{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 独角兽数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 模块准备\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif']=['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "import cufflinks as cf\n",
    "import plotly as py\n",
    "import plotly.graph_objs as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 494 entries, 0 to 493\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   排名            494 non-null    int64 \n",
      " 1   企业名称          494 non-null    object\n",
      " 2   Company Name  494 non-null    object\n",
      " 3   估值（亿人民币）      494 non-null    int64 \n",
      " 4   国家            494 non-null    object\n",
      " 5   城市            494 non-null    object\n",
      " 6   行业            494 non-null    object\n",
      " 7   掌门人/创始人       494 non-null    object\n",
      " 8   成立年份          494 non-null    int64 \n",
      " 9   部分投资机构        494 non-null    object\n",
      "dtypes: int64(3), object(7)\n",
      "memory usage: 38.7+ KB\n"
     ]
    }
   ],
   "source": [
    "# 读取数据\n",
    "df = pd.read_csv (\"hurun_unicorn.tsv\", encoding = \"utf8\", sep=\"\\t\")\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 改变类型  df[[column]] = df[[column]].astype(type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Infor</td>\n",
       "      <td>Infor</td>\n",
       "      <td>3500</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Jim Schaper</td>\n",
       "      <td>2002</td>\n",
       "      <td>Golden Gate Capital, Koch Equity Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>3400</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Adam Bowen, James Monsees, Kevin Burns, Tim Da...</td>\n",
       "      <td>2015</td>\n",
       "      <td>M13, Timothy Davis, Evolution VC Partners, Tig...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>264</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>David A. Steinberg, John Sculley</td>\n",
       "      <td>2007</td>\n",
       "      <td>GPI Capital, GSO Capital Partners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>264</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>半月湾</td>\n",
       "      <td>物流</td>\n",
       "      <td>Keenan Wyrobek, Keller Rinaudo, Will Hetzler</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sequoia Capital, Visionnaire Ventures, Katalys...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>264</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd</td>\n",
       "      <td>2010</td>\n",
       "      <td>IVP (Institutional Venture Partners)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>494 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名                   企业名称           Company Name  估值（亿人民币）  国家   城市  \\\n",
       "0      1                   蚂蚁金服          Ant Financial     10000  中国   杭州   \n",
       "1      2                   字节跳动              Bytedance      5000  中国   北京   \n",
       "2      3                   滴滴出行           Didi Chuxing      3600  中国   北京   \n",
       "3      4                  Infor                  Infor      3500  美国   纽约   \n",
       "4      5              JUUL Labs              JUUL Labs      3400  美国  旧金山   \n",
       "..   ...                    ...                    ...       ...  ..  ...   \n",
       "489  264            Zeta Global            Zeta Global        70  美国   纽约   \n",
       "490  264                  掌门1对1               Zhangmen        70  中国   上海   \n",
       "491  264                     转转             Zhuanzhuan        70  中国   北京   \n",
       "492  264  Zipline International  Zipline International        70  美国  半月湾   \n",
       "493  264           ZipRecruiter           ZipRecruiter        70  美国  洛杉矶   \n",
       "\n",
       "        行业                                            掌门人/创始人  成立年份  \\\n",
       "0     金融科技                                                井贤栋  2014   \n",
       "1    媒体和娱乐                                                张一鸣  2012   \n",
       "2     共享经济                                                 程维  2012   \n",
       "3      云计算                                        Jim Schaper  2002   \n",
       "4      消费品  Adam Bowen, James Monsees, Kevin Burns, Tim Da...  2015   \n",
       "..     ...                                                ...   ...   \n",
       "489   人工智能                   David A. Steinberg, John Sculley  2007   \n",
       "490   教育科技                                                 张翼  2014   \n",
       "491   电子商务                                                姚劲波  2015   \n",
       "492     物流       Keenan Wyrobek, Keller Rinaudo, Will Hetzler  2014   \n",
       "493   电子商务  Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd  2010   \n",
       "\n",
       "                                                部分投资机构  \n",
       "0                                       春华资本、中投海外、红杉资本  \n",
       "1                                  红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2                               腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "3         Golden Gate Capital, Koch Equity Development  \n",
       "4    M13, Timothy Davis, Evolution VC Partners, Tig...  \n",
       "..                                                 ...  \n",
       "489                  GPI Capital, GSO Capital Partners  \n",
       "490                                     顺为资本、达晨创投、华平投资  \n",
       "491                                                 腾讯  \n",
       "492  Sequoia Capital, Visionnaire Ventures, Katalys...  \n",
       "493               IVP (Institutional Venture Partners)  \n",
       "\n",
       "[494 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看完整数据\n",
    "df\n",
    "# df.tail(50) 取后50行数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 可挖掘数据\n",
    "数据：估值、数量   行业  \n",
    "\n",
    "地区对比：\n",
    "属于欧盟国家、亚太、：字典？\n",
    "中国属于不同湾区、一线城市、？  字典？\n",
    "中美对比，一线城市、湾区对比？ 字典？\n",
    "\n",
    "部分投资机构：\n",
    "核心头部投资公司有哪些？\n",
    "核心头部投资公司投了哪些企业？有没有地区倾向？\n",
    "\n",
    "创始人：\n",
    "创始人有几家独角兽企业？拥有独角兽市值？\n",
    "\n",
    "工具：pandas处理数据，分进合（统计平均值，数量，方差，总和），pivot（字符串处理，字典处理，数据结构处理，数据清洗，筛选）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析一、中国城市统计\n",
    "\n",
    "* 1. 统计中国城市，从估值、企业数量和行业分布进行统计\n",
    "* 2. 统计每个中国城市每年的估值、数量发展趋势，并做pivot二维交叉数据趋势图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 统计中国城市，从估值、企业数量和行业分布进行统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>264</td>\n",
       "      <td>网易有道</td>\n",
       "      <td>Youdao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>周枫</td>\n",
       "      <td>2007</td>\n",
       "      <td>君联资本、慕华投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "6      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "10    11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "486  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "487  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "488  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "490  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "491  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构  \n",
       "序号                           \n",
       "0            春华资本、中投海外、红杉资本  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "6       摩根士丹利、中银集团、国泰君安（香港）  \n",
       "10              腾讯、华平投资、淡马锡  \n",
       "..                      ...  \n",
       "486          高瓴资本、晨兴资本、软银中国  \n",
       "487               君联资本、慕华投资  \n",
       "488          华平投资、红杉资本、经纬中国  \n",
       "490          顺为资本、达晨创投、华平投资  \n",
       "491                      腾讯  \n",
       "\n",
       "[206 rows x 10 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index.name=\"序号\"\n",
    "中国=df[df['国家'].isin(['中国'])]\n",
    "中国"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 中国城市的独角兽市值排名情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "      <td>10000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>2012</td>\n",
       "      <td>5140</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>2012</td>\n",
       "      <td>3600</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2011</td>\n",
       "      <td>2700</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2014</td>\n",
       "      <td>1500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>重庆</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>2013</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>金华</td>\n",
       "      <td>新能源汽车</td>\n",
       "      <td>2017</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>香港</td>\n",
       "      <td>物流</td>\n",
       "      <td>2013</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2013</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2016</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>179 rows × 5 columns</p>\n",
       "</div>"
      ],
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       "     城市     行业  成立年份  估值（亿人民币）  企业数量\n",
       "0    杭州   金融科技  2014     10000     1\n",
       "1    北京  媒体和娱乐  2012      5140     3\n",
       "2    北京   共享经济  2012      3600     1\n",
       "3    上海   金融科技  2011      2700     1\n",
       "4    深圳   金融科技  2014      1500     1\n",
       "..   ..    ...   ...       ...   ...\n",
       "174  重庆   电子商务  2013        70     1\n",
       "175  金华  新能源汽车  2017        70     1\n",
       "176  香港     物流  2013        70     1\n",
       "177  香港   金融科技  2013        70     1\n",
       "178  香港   金融科技  2016        70     1\n",
       "\n",
       "[179 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 从估值、企业数量和行业分布进行统计\n",
    "城市情况=中国[['城市','企业名称','估值（亿人民币）','成立年份','行业']]\\\n",
    ".groupby(['城市','行业','成立年份'])\\\n",
    ".agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    ".sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    ".rename ( columns = {\"企业名称\":\"企业数量\"} )\\\n",
    ".reset_index()\n",
    "城市情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
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   "outputs": [
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       "                            \n",
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       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 中国独角兽企业在中国城市的累计市值总额情况\n",
    "城市情况.iplot(kind=\"bar\", x=\"城市\", y=\"估值（亿人民币）\", asFigure=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据结果分析  \n",
    "从城市情况的条形堆叠图来看，北京的独角兽企业累计市值最高，超过20k(亿人民币)，杭州次之。  \n",
    "上海和深圳属于第二梯队，市值累计3至5k(亿人民币)。  \n",
    "天津、南京、广州、成都和香港属于第三梯队，其它城市的独角兽企业较少，市值较低。  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>杭州</th>\n",
       "      <th>金融科技</th>\n",
       "      <td>10290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">北京</th>\n",
       "      <th>媒体和娱乐</th>\n",
       "      <td>6890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>共享经济</th>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>上海</th>\n",
       "      <th>金融科技</th>\n",
       "      <td>3470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>北京</th>\n",
       "      <th>电子商务</th>\n",
       "      <td>2300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>深圳</th>\n",
       "      <th>房地产科技</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>无锡</th>\n",
       "      <th>大数据</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>深圳</th>\n",
       "      <th>人工智能</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>桐乡</th>\n",
       "      <th>新能源汽车</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>上海</th>\n",
       "      <th>云计算</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>87 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          估值（亿人民币）\n",
       "城市 行业             \n",
       "杭州 金融科技      10290\n",
       "北京 媒体和娱乐      6890\n",
       "   共享经济       4040\n",
       "上海 金融科技       3470\n",
       "北京 电子商务       2300\n",
       "...            ...\n",
       "深圳 房地产科技        70\n",
       "无锡 大数据          70\n",
       "深圳 人工智能         70\n",
       "桐乡 新能源汽车        70\n",
       "上海 云计算          70\n",
       "\n",
       "[87 rows x 1 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 中国城市行业估值排行\n",
    "中国城市估值排行=城市情况[['城市','行业','成立年份','企业数量','估值（亿人民币）']]\\\n",
    ".groupby(['城市','行业'])\\\n",
    ".agg({'估值（亿人民币）':'sum'})\\\n",
    ".sort_values(['估值（亿人民币）'],ascending=False)\n",
    "中国城市估值排行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 中国城市企业估值情况\n",
    "x=城市情况['行业']\n",
    "height=城市情况['估值（亿人民币）']\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.grid(axis=\"y\", which=\"major\")  # 生成虚线网格\n",
    "#x、y轴标签\n",
    "plt.xlabel('行业')\n",
    "plt.ylabel('行业估值')\n",
    "#图表标题\n",
    "plt.title('中国城市行业估值情况')\n",
    "plt.bar(x,height,width = 0.6,align='center',color = 'b',alpha=1,bottom=1.2)\n",
    "#设置每个柱子的文本标签,format(b,',')格式化销售额为千位分隔符格式\n",
    "for a,b in zip(x,height):\n",
    "    plt.text(a, b,format(b,''), ha='center', va= 'bottom',fontsize=12,color = 'b',alpha=0.9)\n",
    "#图例\n",
    "plt.legend(['估值（亿人民币）'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据结果分析\n",
    "独角兽企业在金融科技行业企业估值最高，媒体和娱乐行业企业估值次之。  \n",
    "共享经济行业的独角兽企业估值与其它行业相比也有一定的优势，势头很猛，有一定的发展空间。\n",
    "物流、机器人、电子商务、区块链、健康经济行业的企业估值也有一定的分量，也是当代社会比较关注的行业。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 统计每个中国城市每年的估值、数量发展趋势，并做pivot二维交叉数据趋势图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城市</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>行业</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>杭州</td>\n",
       "      <td>2014</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>10000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>北京</td>\n",
       "      <td>2012</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>5140</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>北京</td>\n",
       "      <td>2012</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>3600</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>上海</td>\n",
       "      <td>2011</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>2700</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>深圳</td>\n",
       "      <td>2014</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>1500</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>重庆</td>\n",
       "      <td>2013</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>金华</td>\n",
       "      <td>2017</td>\n",
       "      <td>新能源汽车</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>香港</td>\n",
       "      <td>2013</td>\n",
       "      <td>物流</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>香港</td>\n",
       "      <td>2013</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>香港</td>\n",
       "      <td>2016</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>179 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     城市  成立年份     行业  估值（亿人民币）  企业数量\n",
       "0    杭州  2014   金融科技     10000     1\n",
       "1    北京  2012  媒体和娱乐      5140     3\n",
       "2    北京  2012   共享经济      3600     1\n",
       "3    上海  2011   金融科技      2700     1\n",
       "4    深圳  2014   金融科技      1500     1\n",
       "..   ..   ...    ...       ...   ...\n",
       "174  重庆  2013   电子商务        70     1\n",
       "175  金华  2017  新能源汽车        70     1\n",
       "176  香港  2013     物流        70     1\n",
       "177  香港  2013   金融科技        70     1\n",
       "178  香港  2016   金融科技        70     1\n",
       "\n",
       "[179 rows x 5 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 每个中国城市每年情况\n",
    "数据=中国[['城市','企业名称','估值（亿人民币）','成立年份','行业']]\\\n",
    ".groupby(['城市','成立年份','行业'])\\\n",
    ".agg({'估值（亿人民币）':\"sum\",'企业名称':'count'})\\\n",
    ".sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    ".rename(columns = {\"企业名称\":\"企业数量\"})\\\n",
    ".reset_index()\n",
    "数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"20\" halign=\"left\">估值（亿人民币）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成立年份</th>\n",
       "      <th>2000</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>城市</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>上海</th>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>620.0</td>\n",
       "      <td>2770.0</td>\n",
       "      <td>730.0</td>\n",
       "      <td>340.0</td>\n",
       "      <td>840.0</td>\n",
       "      <td>1350.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>北京</th>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>290.0</td>\n",
       "      <td>940.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>3520.0</td>\n",
       "      <td>9620.0</td>\n",
       "      <td>2600.0</td>\n",
       "      <td>2350.0</td>\n",
       "      <td>1230.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>270.0</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>南京</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>500.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>320.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>台北</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>天津</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>广州</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>张家口</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成都</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>无锡</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>杭州</th>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140.0</td>\n",
       "      <td>400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>240.0</td>\n",
       "      <td>1700.0</td>\n",
       "      <td>10320.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>桐乡</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>武汉</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>深圳</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1200.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140.0</td>\n",
       "      <td>670.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绍兴</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>贵阳</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>重庆</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金华</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>青岛</th>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>香港</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     估值（亿人民币）                                                                  \\\n",
       "成立年份     2000   2001   2002   2003   2004   2005    2006   2007   2008   2009   \n",
       "城市                                                                              \n",
       "上海        NaN   70.0  200.0    NaN    NaN  200.0   250.0  140.0  310.0  270.0   \n",
       "北京        NaN  100.0    NaN  200.0    NaN    NaN   290.0  940.0    NaN  270.0   \n",
       "南京        NaN    NaN    NaN    NaN    NaN    NaN   500.0    NaN  200.0  170.0   \n",
       "台北        NaN    NaN    NaN    NaN    NaN    NaN    70.0    NaN    NaN    NaN   \n",
       "天津        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "广州        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "张家口       NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "成都        NaN    NaN    NaN    NaN    NaN    NaN    70.0    NaN    NaN    NaN   \n",
       "无锡        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "杭州       70.0    NaN    NaN    NaN  100.0    NaN     NaN    NaN    NaN  140.0   \n",
       "桐乡        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "武汉        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "深圳        NaN    NaN    NaN    NaN    NaN    NaN  1200.0  200.0  200.0  100.0   \n",
       "绍兴        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "贵阳        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "重庆        NaN    NaN    NaN    NaN    NaN  100.0     NaN    NaN    NaN    NaN   \n",
       "金华        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "青岛      100.0    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "香港        NaN    NaN    NaN    NaN    NaN    NaN     NaN    NaN    NaN    NaN   \n",
       "\n",
       "                                                                           \\\n",
       "成立年份   2010    2011    2012    2013     2014    2015   2016   2017   2018   \n",
       "城市                                                                          \n",
       "上海    620.0  2770.0   730.0   340.0    840.0  1350.0  800.0  100.0    NaN   \n",
       "北京    280.0  3520.0  9620.0  2600.0   2350.0  1230.0  360.0    NaN  270.0   \n",
       "南京     70.0     NaN     NaN     NaN     70.0   150.0    NaN  320.0   70.0   \n",
       "台北      NaN     NaN     NaN     NaN      NaN     NaN    NaN    NaN    NaN   \n",
       "天津      NaN     NaN     NaN   100.0      NaN   400.0    NaN    NaN  600.0   \n",
       "广州      NaN    70.0    70.0   220.0    300.0   270.0    NaN   70.0    NaN   \n",
       "张家口     NaN     NaN     NaN     NaN      NaN   100.0    NaN    NaN    NaN   \n",
       "成都    150.0    70.0     NaN   100.0      NaN     NaN    NaN    NaN    NaN   \n",
       "无锡     70.0     NaN     NaN     NaN      NaN     NaN    NaN    NaN    NaN   \n",
       "杭州    400.0     NaN   240.0  1700.0  10320.0   320.0    NaN    NaN    NaN   \n",
       "桐乡      NaN     NaN     NaN     NaN     70.0     NaN    NaN    NaN    NaN   \n",
       "武汉      NaN     NaN     NaN     NaN    200.0     NaN    NaN    NaN    NaN   \n",
       "深圳      NaN   140.0   670.0    70.0   1500.0   140.0   70.0    NaN  150.0   \n",
       "绍兴      NaN     NaN     NaN     NaN      NaN     NaN    NaN  100.0    NaN   \n",
       "贵阳      NaN     NaN     NaN     NaN    400.0     NaN    NaN    NaN    NaN   \n",
       "重庆      NaN     NaN     NaN    70.0      NaN     NaN    NaN    NaN    NaN   \n",
       "金华      NaN     NaN     NaN     NaN      NaN     NaN    NaN   70.0    NaN   \n",
       "青岛      NaN     NaN     NaN     NaN      NaN     NaN    NaN    NaN    NaN   \n",
       "香港      NaN     NaN     NaN   140.0    100.0     NaN   70.0  150.0    NaN   \n",
       "\n",
       "             \n",
       "成立年份   2019  \n",
       "城市           \n",
       "上海      NaN  \n",
       "北京    100.0  \n",
       "南京      NaN  \n",
       "台北      NaN  \n",
       "天津      NaN  \n",
       "广州      NaN  \n",
       "张家口     NaN  \n",
       "成都      NaN  \n",
       "无锡      NaN  \n",
       "杭州      NaN  \n",
       "桐乡      NaN  \n",
       "武汉      NaN  \n",
       "深圳      NaN  \n",
       "绍兴      NaN  \n",
       "贵阳      NaN  \n",
       "重庆      NaN  \n",
       "金华      NaN  \n",
       "青岛      NaN  \n",
       "香港      NaN  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 估值发展趋势\n",
    "数据1_pivot=数据.groupby(['城市','成立年份'])\\\n",
    ".agg({\"估值（亿人民币）\":[\"sum\"]})\\\n",
    ".reset_index()\\\n",
    ".pivot(index=\"城市\",columns=\"成立年份\", values=[\"估值（亿人民币）\"])\n",
    "数据1_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 企业市值发展趋势\n",
    "数据1_pivot.T.plot(linestyle='-',marker='o',mfc='w',figsize=(16,8))\n",
    "plt.xlabel('成立年份')        #x轴标题\n",
    "plt.ylabel('市值')         #y轴标题\n",
    "plt.grid(axis=\"y\", which=\"major\") \n",
    "#设置x轴刻度及标签\n",
    "dates=['2000','2001','2002','2003','2004',\n",
    "       '2005','2006','2007','2008','2009',\n",
    "       '2010','2011','2012','2013','2014',\n",
    "       '2015','2016','2017','2018']\n",
    "plt.xticks(range(1,20,1),dates)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>城市</th>\n",
       "      <th>上海</th>\n",
       "      <th>北京</th>\n",
       "      <th>南京</th>\n",
       "      <th>台北</th>\n",
       "      <th>天津</th>\n",
       "      <th>广州</th>\n",
       "      <th>张家口</th>\n",
       "      <th>成都</th>\n",
       "      <th>无锡</th>\n",
       "      <th>杭州</th>\n",
       "      <th>桐乡</th>\n",
       "      <th>武汉</th>\n",
       "      <th>深圳</th>\n",
       "      <th>绍兴</th>\n",
       "      <th>贵阳</th>\n",
       "      <th>重庆</th>\n",
       "      <th>金华</th>\n",
       "      <th>青岛</th>\n",
       "      <th>香港</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>成立年份</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"20\" valign=\"top\">企业数量</th>\n",
       "      <th>2000</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "城市          上海    北京   南京   台北   天津   广州  张家口   成都   无锡   杭州   桐乡   武汉   深圳  \\\n",
       "     成立年份                                                                     \n",
       "企业数量 2000  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  1.0  NaN  NaN  NaN   \n",
       "     2001  1.0   1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "     2002  1.0   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "     2003  NaN   1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "     2004  NaN   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  1.0  NaN  NaN  NaN   \n",
       "     2005  1.0   NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "     2006  2.0   3.0  1.0  1.0  NaN  NaN  NaN  1.0  NaN  NaN  NaN  NaN  2.0   \n",
       "     2007  2.0   3.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  1.0   \n",
       "     2008  4.0   NaN  1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  2.0   \n",
       "     2009  2.0   3.0  2.0  NaN  NaN  NaN  NaN  NaN  NaN  1.0  NaN  NaN  1.0   \n",
       "     2010  4.0   4.0  1.0  NaN  NaN  NaN  NaN  1.0  1.0  1.0  NaN  NaN  NaN   \n",
       "     2011  2.0  12.0  NaN  NaN  NaN  1.0  NaN  1.0  NaN  NaN  NaN  NaN  2.0   \n",
       "     2012  5.0   9.0  NaN  NaN  NaN  1.0  NaN  NaN  NaN  2.0  NaN  NaN  3.0   \n",
       "     2013  2.0   5.0  NaN  NaN  1.0  2.0  NaN  1.0  NaN  3.0  NaN  NaN  1.0   \n",
       "     2014  5.0   9.0  1.0  NaN  NaN  1.0  NaN  NaN  NaN  3.0  1.0  1.0  1.0   \n",
       "     2015  9.0   8.0  1.0  NaN  1.0  2.0  1.0  NaN  NaN  3.0  NaN  NaN  2.0   \n",
       "     2016  2.0   3.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  1.0   \n",
       "     2017  1.0   NaN  1.0  NaN  NaN  1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "     2018  NaN   2.0  1.0  NaN  1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  1.0   \n",
       "     2019  NaN   1.0  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN   \n",
       "\n",
       "城市          绍兴   贵阳   重庆   金华   青岛   香港  \n",
       "     成立年份                                \n",
       "企业数量 2000  NaN  NaN  NaN  NaN  1.0  NaN  \n",
       "     2001  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2002  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2003  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2004  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2005  NaN  NaN  1.0  NaN  NaN  NaN  \n",
       "     2006  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2007  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2008  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2009  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2010  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2011  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2012  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2013  NaN  NaN  1.0  NaN  NaN  2.0  \n",
       "     2014  NaN  1.0  NaN  NaN  NaN  1.0  \n",
       "     2015  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2016  NaN  NaN  NaN  NaN  NaN  1.0  \n",
       "     2017  1.0  NaN  NaN  1.0  NaN  1.0  \n",
       "     2018  NaN  NaN  NaN  NaN  NaN  NaN  \n",
       "     2019  NaN  NaN  NaN  NaN  NaN  NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 企业数量发展趋势\n",
    "数据2_pivot=数据.groupby(['城市','成立年份'])\\\n",
    ".agg({'企业数量':'count'})\\\n",
    ".reset_index()\\\n",
    ".pivot(index=\"城市\",columns=\"成立年份\", values=['企业数量'])\n",
    "数据2_pivot.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 企业数量发展趋势\n",
    "数据2_pivot.T.plot(linestyle='--',marker='o',mfc='w',figsize=(16,8))\n",
    "plt.xlabel('成立年份')        #x轴标题\n",
    "plt.ylabel('企业数量')         #y轴标题\n",
    "plt.grid(axis=\"y\", which=\"major\") \n",
    "#设置x轴刻度及标签\n",
    "dates=['2000','2001','2002','2003','2004',\n",
    "       '2005','2006','2007','2008','2009',\n",
    "       '2010','2011','2012','2013','2014',\n",
    "       '2015','2016','2017','2018']\n",
    "plt.xticks(range(1,20,1),dates)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据结果分析\n",
    "从独角兽企业的市值发展趋势来看，在2009年至2016年企业估值波动较大，期间出现企业估值最大值，市值超过1000亿人民币。    \n",
    "企业估值最高出现在2013年，而企业估值排在第二的独角兽企业位于北京，出现在2011年。  \n",
    "在2004年到2016年，独角兽企业逐渐增多，并且存在时间也较长。  \n",
    "从独角兽企业的数量发展趋势来看，2004至2016年，独角兽企业数量出现较不稳定的波动，整体数量先上升再下降。  \n",
    "在2010年北京地区独角兽企业数量有明显上升，达到12家。  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析二、分析欧盟，亚太和其它地区从估值、企业数量和行业分布进行统计"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 欧盟地区分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>50</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>350</td>\n",
       "      <td>英国</td>\n",
       "      <td>曼彻斯特</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>John Gallemore, Matthew Moulding</td>\n",
       "      <td>2004</td>\n",
       "      <td>Artemis, Lewis Trust Group, Kohlberg Kravis Ro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>300</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Christian Bertermann, Hakan Koc</td>\n",
       "      <td>2012</td>\n",
       "      <td>DN Capital, Piton Capital, DST Global, Princev...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>57</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>300</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Niklas Adalberth, Sebastian Siemiatkowski, Vic...</td>\n",
       "      <td>2005</td>\n",
       "      <td>Investment AB Öresund, Sequoia Capital, Genera...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>57</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>300</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Kristo Kaarmann, Taavet Hinrikus</td>\n",
       "      <td>2011</td>\n",
       "      <td>Seedcamp, IA Ventures , Valar Ventures, Index ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>83</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>250</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jason Austin, Lex Greensill</td>\n",
       "      <td>2011</td>\n",
       "      <td>General Atlantic, SoftBank Investment Advisers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>84</td>\n",
       "      <td>Monzo</td>\n",
       "      <td>Monzo</td>\n",
       "      <td>200</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Gary Dolman, Jason Bates, Jonas Huckestein, Pa...</td>\n",
       "      <td>2015</td>\n",
       "      <td>Y Combinator, Passion Capital, Thrive Capital,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>84</td>\n",
       "      <td>N26</td>\n",
       "      <td>N26</td>\n",
       "      <td>200</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Maximilian Tayenthal, Valentin Stalf</td>\n",
       "      <td>2013</td>\n",
       "      <td>Earlybird Venture Capital, Valar Ventures, Hor...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>84</td>\n",
       "      <td>OakNorth</td>\n",
       "      <td>OakNorth</td>\n",
       "      <td>200</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Joel Perlman, Rishi Khosla</td>\n",
       "      <td>2013</td>\n",
       "      <td>EDBI, SoftBank Investment Advisers, NIBC Bank ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>138</td>\n",
       "      <td>BenevolentAI</td>\n",
       "      <td>BenevolentAI</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Brent Gutekunst, Ivan Griffin, Ken Mulvany, Mi...</td>\n",
       "      <td>2013</td>\n",
       "      <td>Woodford Investment Management</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>138</td>\n",
       "      <td>Binance</td>\n",
       "      <td>Binance</td>\n",
       "      <td>150</td>\n",
       "      <td>马耳他</td>\n",
       "      <td>-</td>\n",
       "      <td>区块链</td>\n",
       "      <td>赵长鹏、何一</td>\n",
       "      <td>2017</td>\n",
       "      <td>Vertex Ventures, Black Hole Capital, Funcity C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>138</td>\n",
       "      <td>BlaBlaCar</td>\n",
       "      <td>BlaBlaCar</td>\n",
       "      <td>150</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Francis Nappez, Frédéric Mazzella, Nicolas Bru...</td>\n",
       "      <td>2006</td>\n",
       "      <td>Accel, Index Ventures, Insight Partners, Barin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>138</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Guillaume Pousaz</td>\n",
       "      <td>2012</td>\n",
       "      <td>DST Global , Insight Partners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>138</td>\n",
       "      <td>CureVac</td>\n",
       "      <td>CureVac</td>\n",
       "      <td>150</td>\n",
       "      <td>德国</td>\n",
       "      <td>巴登符腾堡州</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Ingmar Hoerr</td>\n",
       "      <td>2000</td>\n",
       "      <td>DH Capital, Dievini Hopp Biotech Holding, OH B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>138</td>\n",
       "      <td>Deliveroo</td>\n",
       "      <td>Deliveroo</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>物流</td>\n",
       "      <td>Greg Orlowski, William Shu</td>\n",
       "      <td>2012</td>\n",
       "      <td>Bridgepoint, Fidelity Management and Research ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>138</td>\n",
       "      <td>FlixBus</td>\n",
       "      <td>FlixBus</td>\n",
       "      <td>150</td>\n",
       "      <td>德国</td>\n",
       "      <td>慕尼黑</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>André Schwämmlein, Daniel Krauss, Jochen Engert</td>\n",
       "      <td>2011</td>\n",
       "      <td>Permira, TCV, Silver Lake Partners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>138</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Nigel Toon, Simon Knowles</td>\n",
       "      <td>2016</td>\n",
       "      <td>Amadeus Capital Partners, Atomico, Sequoia Cap...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>138</td>\n",
       "      <td>Improbable</td>\n",
       "      <td>Improbable</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>游戏</td>\n",
       "      <td>Herman Narula, Peter Lipka, Rob Whitehead</td>\n",
       "      <td>2012</td>\n",
       "      <td>SoftBank Investment Advisers, NetEase, Amadeus...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>138</td>\n",
       "      <td>Kaseya</td>\n",
       "      <td>Kaseya</td>\n",
       "      <td>150</td>\n",
       "      <td>爱尔兰</td>\n",
       "      <td>都柏林</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Gerald Blackie</td>\n",
       "      <td>2000</td>\n",
       "      <td>TPG, Ireland Strategic Investment Fund, Insigh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>138</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>150</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Paolo Cerruti, Peter Carlsson</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen Group, Goldman Sachs, Seimens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>138</td>\n",
       "      <td>Oxford Nanopore Technologies</td>\n",
       "      <td>Oxford Nanopore Technologies</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>牛津</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Gordon Sanghera, Hagan Bayley</td>\n",
       "      <td>2005</td>\n",
       "      <td>Amgen, IP Group Plc, Woodford Investment Manag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>138</td>\n",
       "      <td>Revolut</td>\n",
       "      <td>Revolut</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Nikolay Storonsky, Vlad Yatsenko</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mastercard Start Path, Balderton Capital, Trip...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>264</td>\n",
       "      <td>About You</td>\n",
       "      <td>About You</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>汉堡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Sebastian Betz, Tarek Muller</td>\n",
       "      <td>2014</td>\n",
       "      <td>SevenVentures, Bestseller</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>264</td>\n",
       "      <td>Bolt</td>\n",
       "      <td>Bolt</td>\n",
       "      <td>70</td>\n",
       "      <td>爱沙尼亚</td>\n",
       "      <td>塔林</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Markus Villig, Martin Villig, Oliver Leisalu</td>\n",
       "      <td>2013</td>\n",
       "      <td>Didi Chuxing, Daimler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>264</td>\n",
       "      <td>Cabify</td>\n",
       "      <td>Cabify</td>\n",
       "      <td>70</td>\n",
       "      <td>西班牙</td>\n",
       "      <td>马德里</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Adrian Merino, Francisco Montero, Juan De Anto...</td>\n",
       "      <td>2011</td>\n",
       "      <td>Kevin Laws, Seaya Ventures, Rakuten Capital, I...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>264</td>\n",
       "      <td>Deezer</td>\n",
       "      <td>Deezer</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>Daniel Marhely, Jonathan Benassaya</td>\n",
       "      <td>2006</td>\n",
       "      <td>Access Industries, Idinvest Partners, Kingdom ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>264</td>\n",
       "      <td>Doctolib</td>\n",
       "      <td>Doctolib</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>健康科技</td>\n",
       "      <td>Franck Tetzlaff, Ivan Schneider, Jessy Bernal,...</td>\n",
       "      <td>2013</td>\n",
       "      <td>Kerala Ventures, Accel, Bpifrance, Eurazeo, Ge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>264</td>\n",
       "      <td>GetYourGuide</td>\n",
       "      <td>GetYourGuide</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Jochen Mattes, Johannes Reck, Martin Sieber, P...</td>\n",
       "      <td>2009</td>\n",
       "      <td>PROfounders Capital, Highland Europe , Fritz D...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>342</th>\n",
       "      <td>264</td>\n",
       "      <td>Global Fashion Group</td>\n",
       "      <td>Global Fashion Group</td>\n",
       "      <td>70</td>\n",
       "      <td>卢森堡</td>\n",
       "      <td>卢森堡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>-</td>\n",
       "      <td>2014</td>\n",
       "      <td>Lewis trust Group. Rocket Internet, Kinnevik AB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>264</td>\n",
       "      <td>HMD</td>\n",
       "      <td>HMD</td>\n",
       "      <td>70</td>\n",
       "      <td>芬兰</td>\n",
       "      <td>赫尔辛基</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Jean-Francois Baril</td>\n",
       "      <td>2016</td>\n",
       "      <td>Ginko Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>264</td>\n",
       "      <td>Meero</td>\n",
       "      <td>Meero</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Thomas Rebaud</td>\n",
       "      <td>2016</td>\n",
       "      <td>Avenir Growth Capital, Eurazeo Prime Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>264</td>\n",
       "      <td>Omio</td>\n",
       "      <td>Omio</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Naren Shaam</td>\n",
       "      <td>2012</td>\n",
       "      <td>Goldman Sachs Investment Partners, Kleiner Per...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>264</td>\n",
       "      <td>Ovo Energy</td>\n",
       "      <td>Ovo Energy</td>\n",
       "      <td>70</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Stephen Fitzpatrick</td>\n",
       "      <td>2009</td>\n",
       "      <td>Mitsubishi Corp</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名                          企业名称                  Company Name  \\\n",
       "序号                                                                     \n",
       "55    50                 The Hut Group                 The Hut Group   \n",
       "56    57                   Auto1 Group                   Auto1 Group   \n",
       "62    57                        Klarna                        Klarna   \n",
       "73    57                  TransferWise                  TransferWise   \n",
       "82    83                     Greensill                     Greensill   \n",
       "107   84                         Monzo                         Monzo   \n",
       "108   84                           N26                           N26   \n",
       "110   84                      OakNorth                      OakNorth   \n",
       "145  138                  BenevolentAI                  BenevolentAI   \n",
       "147  138                       Binance                       Binance   \n",
       "149  138                     BlaBlaCar                     BlaBlaCar   \n",
       "157  138                  Checkout.com                  Checkout.com   \n",
       "160  138                       CureVac                       CureVac   \n",
       "164  138                     Deliveroo                     Deliveroo   \n",
       "169  138                       FlixBus                       FlixBus   \n",
       "172  138                     Graphcore                     Graphcore   \n",
       "177  138                    Improbable                    Improbable   \n",
       "182  138                        Kaseya                        Kaseya   \n",
       "196  138                     Northvolt                     Northvolt   \n",
       "197  138  Oxford Nanopore Technologies  Oxford Nanopore Technologies   \n",
       "207  138                       Revolut                       Revolut   \n",
       "269  264                     About You                     About You   \n",
       "290  264                          Bolt                          Bolt   \n",
       "297  264                        Cabify                        Cabify   \n",
       "317  264                        Deezer                        Deezer   \n",
       "320  264                      Doctolib                      Doctolib   \n",
       "339  264                  GetYourGuide                  GetYourGuide   \n",
       "342  264          Global Fashion Group          Global Fashion Group   \n",
       "349  264                           HMD                           HMD   \n",
       "396  264                         Meero                         Meero   \n",
       "411  264                          Omio                          Omio   \n",
       "418  264                    Ovo Energy                    Ovo Energy   \n",
       "\n",
       "     估值（亿人民币）    国家      城市     行业  \\\n",
       "序号                                   \n",
       "55        350    英国    曼彻斯特   电子商务   \n",
       "56        300    德国      柏林   电子商务   \n",
       "62        300    瑞典   斯德哥尔摩   金融科技   \n",
       "73        300    英国      伦敦   金融科技   \n",
       "82        250    英国      伦敦   金融科技   \n",
       "107       200    英国      伦敦   金融科技   \n",
       "108       200    德国      柏林   金融科技   \n",
       "110       200    英国      伦敦   金融科技   \n",
       "145       150    英国      伦敦   人工智能   \n",
       "147       150   马耳他       -    区块链   \n",
       "149       150    法国      巴黎   共享经济   \n",
       "157       150    英国      伦敦   金融科技   \n",
       "160       150    德国  巴登符腾堡州   生命科学   \n",
       "164       150    英国      伦敦     物流   \n",
       "169       150    德国     慕尼黑   电子商务   \n",
       "172       150    英国   布里斯托尔   人工智能   \n",
       "177       150    英国      伦敦     游戏   \n",
       "182       150   爱尔兰     都柏林    云计算   \n",
       "196       150    瑞典   斯德哥尔摩    新能源   \n",
       "197       150    英国      牛津   生命科学   \n",
       "207       150    英国      伦敦   金融科技   \n",
       "269        70    德国      汉堡   电子商务   \n",
       "290        70  爱沙尼亚      塔林   共享经济   \n",
       "297        70   西班牙     马德里   共享经济   \n",
       "317        70    法国      巴黎  媒体和娱乐   \n",
       "320        70    法国      巴黎   健康科技   \n",
       "339        70    德国      柏林   电子商务   \n",
       "342        70   卢森堡     卢森堡   电子商务   \n",
       "349        70    芬兰    赫尔辛基    消费品   \n",
       "396        70    法国      巴黎   人工智能   \n",
       "411        70    德国      柏林   电子商务   \n",
       "418        70    英国   布里斯托尔    新能源   \n",
       "\n",
       "                                               掌门人/创始人  成立年份  \\\n",
       "序号                                                             \n",
       "55                    John Gallemore, Matthew Moulding  2004   \n",
       "56                     Christian Bertermann, Hakan Koc  2012   \n",
       "62   Niklas Adalberth, Sebastian Siemiatkowski, Vic...  2005   \n",
       "73                    Kristo Kaarmann, Taavet Hinrikus  2011   \n",
       "82                         Jason Austin, Lex Greensill  2011   \n",
       "107  Gary Dolman, Jason Bates, Jonas Huckestein, Pa...  2015   \n",
       "108               Maximilian Tayenthal, Valentin Stalf  2013   \n",
       "110                         Joel Perlman, Rishi Khosla  2013   \n",
       "145  Brent Gutekunst, Ivan Griffin, Ken Mulvany, Mi...  2013   \n",
       "147                                             赵长鹏、何一  2017   \n",
       "149  Francis Nappez, Frédéric Mazzella, Nicolas Bru...  2006   \n",
       "157                                   Guillaume Pousaz  2012   \n",
       "160                                       Ingmar Hoerr  2000   \n",
       "164                         Greg Orlowski, William Shu  2012   \n",
       "169    André Schwämmlein, Daniel Krauss, Jochen Engert  2011   \n",
       "172                          Nigel Toon, Simon Knowles  2016   \n",
       "177          Herman Narula, Peter Lipka, Rob Whitehead  2012   \n",
       "182                                     Gerald Blackie  2000   \n",
       "196                      Paolo Cerruti, Peter Carlsson  2016   \n",
       "197                      Gordon Sanghera, Hagan Bayley  2005   \n",
       "207                   Nikolay Storonsky, Vlad Yatsenko  2015   \n",
       "269                       Sebastian Betz, Tarek Muller  2014   \n",
       "290       Markus Villig, Martin Villig, Oliver Leisalu  2013   \n",
       "297  Adrian Merino, Francisco Montero, Juan De Anto...  2011   \n",
       "317                 Daniel Marhely, Jonathan Benassaya  2006   \n",
       "320  Franck Tetzlaff, Ivan Schneider, Jessy Bernal,...  2013   \n",
       "339  Jochen Mattes, Johannes Reck, Martin Sieber, P...  2009   \n",
       "342                                                  -  2014   \n",
       "349                                Jean-Francois Baril  2016   \n",
       "396                                      Thomas Rebaud  2016   \n",
       "411                                        Naren Shaam  2012   \n",
       "418                                Stephen Fitzpatrick  2009   \n",
       "\n",
       "                                                部分投资机构  \n",
       "序号                                                      \n",
       "55   Artemis, Lewis Trust Group, Kohlberg Kravis Ro...  \n",
       "56   DN Capital, Piton Capital, DST Global, Princev...  \n",
       "62   Investment AB Öresund, Sequoia Capital, Genera...  \n",
       "73   Seedcamp, IA Ventures , Valar Ventures, Index ...  \n",
       "82      General Atlantic, SoftBank Investment Advisers  \n",
       "107  Y Combinator, Passion Capital, Thrive Capital,...  \n",
       "108  Earlybird Venture Capital, Valar Ventures, Hor...  \n",
       "110  EDBI, SoftBank Investment Advisers, NIBC Bank ...  \n",
       "145                     Woodford Investment Management  \n",
       "147  Vertex Ventures, Black Hole Capital, Funcity C...  \n",
       "149  Accel, Index Ventures, Insight Partners, Barin...  \n",
       "157                      DST Global , Insight Partners  \n",
       "160  DH Capital, Dievini Hopp Biotech Holding, OH B...  \n",
       "164  Bridgepoint, Fidelity Management and Research ...  \n",
       "169                 Permira, TCV, Silver Lake Partners  \n",
       "172  Amadeus Capital Partners, Atomico, Sequoia Cap...  \n",
       "177  SoftBank Investment Advisers, NetEase, Amadeus...  \n",
       "182  TPG, Ireland Strategic Investment Fund, Insigh...  \n",
       "196           Volkswagen Group, Goldman Sachs, Seimens  \n",
       "197  Amgen, IP Group Plc, Woodford Investment Manag...  \n",
       "207  Mastercard Start Path, Balderton Capital, Trip...  \n",
       "269                          SevenVentures, Bestseller  \n",
       "290                              Didi Chuxing, Daimler  \n",
       "297  Kevin Laws, Seaya Ventures, Rakuten Capital, I...  \n",
       "317  Access Industries, Idinvest Partners, Kingdom ...  \n",
       "320  Kerala Ventures, Accel, Bpifrance, Eurazeo, Ge...  \n",
       "339  PROfounders Capital, Highland Europe , Fritz D...  \n",
       "342    Lewis trust Group. Rocket Internet, Kinnevik AB  \n",
       "349                                     Ginko Ventures  \n",
       "396      Avenir Growth Capital, Eurazeo Prime Ventures  \n",
       "411  Goldman Sachs Investment Partners, Kleiner Per...  \n",
       "418                                    Mitsubishi Corp  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "欧盟国家=[\"法国\",\"德国\",\"意大利\",\"荷兰\",\"比利时\",\"卢森堡\",\"爱尔兰\",\"英国\",\"丹麦\",\"希腊\",\"西班牙\",\"葡萄牙\",\"芬兰\",\"瑞典\",\"奥地利\",\"爱沙尼亚\",\"拉脱维亚\",\"立陶宛\",\"波兰\",\"捷克\",\"匈牙利\",\"斯洛伐克\",\"斯洛文尼亚\",\"马耳他\",\"塞浦路斯\",\"罗马尼亚\",\"保加利亚\"]\n",
    "df.index.name=\"序号\"\n",
    "欧盟=df[df['国家'].isin(欧盟国家)]\n",
    "欧盟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>地区分布</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>50</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>350</td>\n",
       "      <td>英国</td>\n",
       "      <td>曼彻斯特</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>John Gallemore, Matthew Moulding</td>\n",
       "      <td>2004</td>\n",
       "      <td>Artemis, Lewis Trust Group, Kohlberg Kravis Ro...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>300</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Christian Bertermann, Hakan Koc</td>\n",
       "      <td>2012</td>\n",
       "      <td>DN Capital, Piton Capital, DST Global, Princev...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>57</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>300</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Niklas Adalberth, Sebastian Siemiatkowski, Vic...</td>\n",
       "      <td>2005</td>\n",
       "      <td>Investment AB Öresund, Sequoia Capital, Genera...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>57</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>300</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Kristo Kaarmann, Taavet Hinrikus</td>\n",
       "      <td>2011</td>\n",
       "      <td>Seedcamp, IA Ventures , Valar Ventures, Index ...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>83</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>250</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jason Austin, Lex Greensill</td>\n",
       "      <td>2011</td>\n",
       "      <td>General Atlantic, SoftBank Investment Advisers</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>84</td>\n",
       "      <td>Monzo</td>\n",
       "      <td>Monzo</td>\n",
       "      <td>200</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Gary Dolman, Jason Bates, Jonas Huckestein, Pa...</td>\n",
       "      <td>2015</td>\n",
       "      <td>Y Combinator, Passion Capital, Thrive Capital,...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>84</td>\n",
       "      <td>N26</td>\n",
       "      <td>N26</td>\n",
       "      <td>200</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Maximilian Tayenthal, Valentin Stalf</td>\n",
       "      <td>2013</td>\n",
       "      <td>Earlybird Venture Capital, Valar Ventures, Hor...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>84</td>\n",
       "      <td>OakNorth</td>\n",
       "      <td>OakNorth</td>\n",
       "      <td>200</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Joel Perlman, Rishi Khosla</td>\n",
       "      <td>2013</td>\n",
       "      <td>EDBI, SoftBank Investment Advisers, NIBC Bank ...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>138</td>\n",
       "      <td>BenevolentAI</td>\n",
       "      <td>BenevolentAI</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Brent Gutekunst, Ivan Griffin, Ken Mulvany, Mi...</td>\n",
       "      <td>2013</td>\n",
       "      <td>Woodford Investment Management</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>138</td>\n",
       "      <td>Binance</td>\n",
       "      <td>Binance</td>\n",
       "      <td>150</td>\n",
       "      <td>马耳他</td>\n",
       "      <td>-</td>\n",
       "      <td>区块链</td>\n",
       "      <td>赵长鹏、何一</td>\n",
       "      <td>2017</td>\n",
       "      <td>Vertex Ventures, Black Hole Capital, Funcity C...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>138</td>\n",
       "      <td>BlaBlaCar</td>\n",
       "      <td>BlaBlaCar</td>\n",
       "      <td>150</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Francis Nappez, Frédéric Mazzella, Nicolas Bru...</td>\n",
       "      <td>2006</td>\n",
       "      <td>Accel, Index Ventures, Insight Partners, Barin...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>138</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>Checkout.com</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Guillaume Pousaz</td>\n",
       "      <td>2012</td>\n",
       "      <td>DST Global , Insight Partners</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>138</td>\n",
       "      <td>CureVac</td>\n",
       "      <td>CureVac</td>\n",
       "      <td>150</td>\n",
       "      <td>德国</td>\n",
       "      <td>巴登符腾堡州</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Ingmar Hoerr</td>\n",
       "      <td>2000</td>\n",
       "      <td>DH Capital, Dievini Hopp Biotech Holding, OH B...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>138</td>\n",
       "      <td>Deliveroo</td>\n",
       "      <td>Deliveroo</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>物流</td>\n",
       "      <td>Greg Orlowski, William Shu</td>\n",
       "      <td>2012</td>\n",
       "      <td>Bridgepoint, Fidelity Management and Research ...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>138</td>\n",
       "      <td>FlixBus</td>\n",
       "      <td>FlixBus</td>\n",
       "      <td>150</td>\n",
       "      <td>德国</td>\n",
       "      <td>慕尼黑</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>André Schwämmlein, Daniel Krauss, Jochen Engert</td>\n",
       "      <td>2011</td>\n",
       "      <td>Permira, TCV, Silver Lake Partners</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>138</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Nigel Toon, Simon Knowles</td>\n",
       "      <td>2016</td>\n",
       "      <td>Amadeus Capital Partners, Atomico, Sequoia Cap...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>138</td>\n",
       "      <td>Improbable</td>\n",
       "      <td>Improbable</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>游戏</td>\n",
       "      <td>Herman Narula, Peter Lipka, Rob Whitehead</td>\n",
       "      <td>2012</td>\n",
       "      <td>SoftBank Investment Advisers, NetEase, Amadeus...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>138</td>\n",
       "      <td>Kaseya</td>\n",
       "      <td>Kaseya</td>\n",
       "      <td>150</td>\n",
       "      <td>爱尔兰</td>\n",
       "      <td>都柏林</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Gerald Blackie</td>\n",
       "      <td>2000</td>\n",
       "      <td>TPG, Ireland Strategic Investment Fund, Insigh...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>138</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>150</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Paolo Cerruti, Peter Carlsson</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen Group, Goldman Sachs, Seimens</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>138</td>\n",
       "      <td>Oxford Nanopore Technologies</td>\n",
       "      <td>Oxford Nanopore Technologies</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>牛津</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Gordon Sanghera, Hagan Bayley</td>\n",
       "      <td>2005</td>\n",
       "      <td>Amgen, IP Group Plc, Woodford Investment Manag...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>138</td>\n",
       "      <td>Revolut</td>\n",
       "      <td>Revolut</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Nikolay Storonsky, Vlad Yatsenko</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mastercard Start Path, Balderton Capital, Trip...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>264</td>\n",
       "      <td>About You</td>\n",
       "      <td>About You</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>汉堡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Sebastian Betz, Tarek Muller</td>\n",
       "      <td>2014</td>\n",
       "      <td>SevenVentures, Bestseller</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>264</td>\n",
       "      <td>Bolt</td>\n",
       "      <td>Bolt</td>\n",
       "      <td>70</td>\n",
       "      <td>爱沙尼亚</td>\n",
       "      <td>塔林</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Markus Villig, Martin Villig, Oliver Leisalu</td>\n",
       "      <td>2013</td>\n",
       "      <td>Didi Chuxing, Daimler</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>264</td>\n",
       "      <td>Cabify</td>\n",
       "      <td>Cabify</td>\n",
       "      <td>70</td>\n",
       "      <td>西班牙</td>\n",
       "      <td>马德里</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Adrian Merino, Francisco Montero, Juan De Anto...</td>\n",
       "      <td>2011</td>\n",
       "      <td>Kevin Laws, Seaya Ventures, Rakuten Capital, I...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>264</td>\n",
       "      <td>Deezer</td>\n",
       "      <td>Deezer</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>Daniel Marhely, Jonathan Benassaya</td>\n",
       "      <td>2006</td>\n",
       "      <td>Access Industries, Idinvest Partners, Kingdom ...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>264</td>\n",
       "      <td>Doctolib</td>\n",
       "      <td>Doctolib</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>健康科技</td>\n",
       "      <td>Franck Tetzlaff, Ivan Schneider, Jessy Bernal,...</td>\n",
       "      <td>2013</td>\n",
       "      <td>Kerala Ventures, Accel, Bpifrance, Eurazeo, Ge...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>264</td>\n",
       "      <td>GetYourGuide</td>\n",
       "      <td>GetYourGuide</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Jochen Mattes, Johannes Reck, Martin Sieber, P...</td>\n",
       "      <td>2009</td>\n",
       "      <td>PROfounders Capital, Highland Europe , Fritz D...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>342</th>\n",
       "      <td>264</td>\n",
       "      <td>Global Fashion Group</td>\n",
       "      <td>Global Fashion Group</td>\n",
       "      <td>70</td>\n",
       "      <td>卢森堡</td>\n",
       "      <td>卢森堡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>-</td>\n",
       "      <td>2014</td>\n",
       "      <td>Lewis trust Group. Rocket Internet, Kinnevik AB</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>264</td>\n",
       "      <td>HMD</td>\n",
       "      <td>HMD</td>\n",
       "      <td>70</td>\n",
       "      <td>芬兰</td>\n",
       "      <td>赫尔辛基</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Jean-Francois Baril</td>\n",
       "      <td>2016</td>\n",
       "      <td>Ginko Ventures</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>264</td>\n",
       "      <td>Meero</td>\n",
       "      <td>Meero</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Thomas Rebaud</td>\n",
       "      <td>2016</td>\n",
       "      <td>Avenir Growth Capital, Eurazeo Prime Ventures</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>264</td>\n",
       "      <td>Omio</td>\n",
       "      <td>Omio</td>\n",
       "      <td>70</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Naren Shaam</td>\n",
       "      <td>2012</td>\n",
       "      <td>Goldman Sachs Investment Partners, Kleiner Per...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>264</td>\n",
       "      <td>Ovo Energy</td>\n",
       "      <td>Ovo Energy</td>\n",
       "      <td>70</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Stephen Fitzpatrick</td>\n",
       "      <td>2009</td>\n",
       "      <td>Mitsubishi Corp</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名                          企业名称                  Company Name  \\\n",
       "序号                                                                     \n",
       "55    50                 The Hut Group                 The Hut Group   \n",
       "56    57                   Auto1 Group                   Auto1 Group   \n",
       "62    57                        Klarna                        Klarna   \n",
       "73    57                  TransferWise                  TransferWise   \n",
       "82    83                     Greensill                     Greensill   \n",
       "107   84                         Monzo                         Monzo   \n",
       "108   84                           N26                           N26   \n",
       "110   84                      OakNorth                      OakNorth   \n",
       "145  138                  BenevolentAI                  BenevolentAI   \n",
       "147  138                       Binance                       Binance   \n",
       "149  138                     BlaBlaCar                     BlaBlaCar   \n",
       "157  138                  Checkout.com                  Checkout.com   \n",
       "160  138                       CureVac                       CureVac   \n",
       "164  138                     Deliveroo                     Deliveroo   \n",
       "169  138                       FlixBus                       FlixBus   \n",
       "172  138                     Graphcore                     Graphcore   \n",
       "177  138                    Improbable                    Improbable   \n",
       "182  138                        Kaseya                        Kaseya   \n",
       "196  138                     Northvolt                     Northvolt   \n",
       "197  138  Oxford Nanopore Technologies  Oxford Nanopore Technologies   \n",
       "207  138                       Revolut                       Revolut   \n",
       "269  264                     About You                     About You   \n",
       "290  264                          Bolt                          Bolt   \n",
       "297  264                        Cabify                        Cabify   \n",
       "317  264                        Deezer                        Deezer   \n",
       "320  264                      Doctolib                      Doctolib   \n",
       "339  264                  GetYourGuide                  GetYourGuide   \n",
       "342  264          Global Fashion Group          Global Fashion Group   \n",
       "349  264                           HMD                           HMD   \n",
       "396  264                         Meero                         Meero   \n",
       "411  264                          Omio                          Omio   \n",
       "418  264                    Ovo Energy                    Ovo Energy   \n",
       "\n",
       "     估值（亿人民币）    国家      城市     行业  \\\n",
       "序号                                   \n",
       "55        350    英国    曼彻斯特   电子商务   \n",
       "56        300    德国      柏林   电子商务   \n",
       "62        300    瑞典   斯德哥尔摩   金融科技   \n",
       "73        300    英国      伦敦   金融科技   \n",
       "82        250    英国      伦敦   金融科技   \n",
       "107       200    英国      伦敦   金融科技   \n",
       "108       200    德国      柏林   金融科技   \n",
       "110       200    英国      伦敦   金融科技   \n",
       "145       150    英国      伦敦   人工智能   \n",
       "147       150   马耳他       -    区块链   \n",
       "149       150    法国      巴黎   共享经济   \n",
       "157       150    英国      伦敦   金融科技   \n",
       "160       150    德国  巴登符腾堡州   生命科学   \n",
       "164       150    英国      伦敦     物流   \n",
       "169       150    德国     慕尼黑   电子商务   \n",
       "172       150    英国   布里斯托尔   人工智能   \n",
       "177       150    英国      伦敦     游戏   \n",
       "182       150   爱尔兰     都柏林    云计算   \n",
       "196       150    瑞典   斯德哥尔摩    新能源   \n",
       "197       150    英国      牛津   生命科学   \n",
       "207       150    英国      伦敦   金融科技   \n",
       "269        70    德国      汉堡   电子商务   \n",
       "290        70  爱沙尼亚      塔林   共享经济   \n",
       "297        70   西班牙     马德里   共享经济   \n",
       "317        70    法国      巴黎  媒体和娱乐   \n",
       "320        70    法国      巴黎   健康科技   \n",
       "339        70    德国      柏林   电子商务   \n",
       "342        70   卢森堡     卢森堡   电子商务   \n",
       "349        70    芬兰    赫尔辛基    消费品   \n",
       "396        70    法国      巴黎   人工智能   \n",
       "411        70    德国      柏林   电子商务   \n",
       "418        70    英国   布里斯托尔    新能源   \n",
       "\n",
       "                                               掌门人/创始人  成立年份  \\\n",
       "序号                                                             \n",
       "55                    John Gallemore, Matthew Moulding  2004   \n",
       "56                     Christian Bertermann, Hakan Koc  2012   \n",
       "62   Niklas Adalberth, Sebastian Siemiatkowski, Vic...  2005   \n",
       "73                    Kristo Kaarmann, Taavet Hinrikus  2011   \n",
       "82                         Jason Austin, Lex Greensill  2011   \n",
       "107  Gary Dolman, Jason Bates, Jonas Huckestein, Pa...  2015   \n",
       "108               Maximilian Tayenthal, Valentin Stalf  2013   \n",
       "110                         Joel Perlman, Rishi Khosla  2013   \n",
       "145  Brent Gutekunst, Ivan Griffin, Ken Mulvany, Mi...  2013   \n",
       "147                                             赵长鹏、何一  2017   \n",
       "149  Francis Nappez, Frédéric Mazzella, Nicolas Bru...  2006   \n",
       "157                                   Guillaume Pousaz  2012   \n",
       "160                                       Ingmar Hoerr  2000   \n",
       "164                         Greg Orlowski, William Shu  2012   \n",
       "169    André Schwämmlein, Daniel Krauss, Jochen Engert  2011   \n",
       "172                          Nigel Toon, Simon Knowles  2016   \n",
       "177          Herman Narula, Peter Lipka, Rob Whitehead  2012   \n",
       "182                                     Gerald Blackie  2000   \n",
       "196                      Paolo Cerruti, Peter Carlsson  2016   \n",
       "197                      Gordon Sanghera, Hagan Bayley  2005   \n",
       "207                   Nikolay Storonsky, Vlad Yatsenko  2015   \n",
       "269                       Sebastian Betz, Tarek Muller  2014   \n",
       "290       Markus Villig, Martin Villig, Oliver Leisalu  2013   \n",
       "297  Adrian Merino, Francisco Montero, Juan De Anto...  2011   \n",
       "317                 Daniel Marhely, Jonathan Benassaya  2006   \n",
       "320  Franck Tetzlaff, Ivan Schneider, Jessy Bernal,...  2013   \n",
       "339  Jochen Mattes, Johannes Reck, Martin Sieber, P...  2009   \n",
       "342                                                  -  2014   \n",
       "349                                Jean-Francois Baril  2016   \n",
       "396                                      Thomas Rebaud  2016   \n",
       "411                                        Naren Shaam  2012   \n",
       "418                                Stephen Fitzpatrick  2009   \n",
       "\n",
       "                                                部分投资机构 地区分布  \n",
       "序号                                                           \n",
       "55   Artemis, Lewis Trust Group, Kohlberg Kravis Ro...   欧盟  \n",
       "56   DN Capital, Piton Capital, DST Global, Princev...   欧盟  \n",
       "62   Investment AB Öresund, Sequoia Capital, Genera...   欧盟  \n",
       "73   Seedcamp, IA Ventures , Valar Ventures, Index ...   欧盟  \n",
       "82      General Atlantic, SoftBank Investment Advisers   欧盟  \n",
       "107  Y Combinator, Passion Capital, Thrive Capital,...   欧盟  \n",
       "108  Earlybird Venture Capital, Valar Ventures, Hor...   欧盟  \n",
       "110  EDBI, SoftBank Investment Advisers, NIBC Bank ...   欧盟  \n",
       "145                     Woodford Investment Management   欧盟  \n",
       "147  Vertex Ventures, Black Hole Capital, Funcity C...   欧盟  \n",
       "149  Accel, Index Ventures, Insight Partners, Barin...   欧盟  \n",
       "157                      DST Global , Insight Partners   欧盟  \n",
       "160  DH Capital, Dievini Hopp Biotech Holding, OH B...   欧盟  \n",
       "164  Bridgepoint, Fidelity Management and Research ...   欧盟  \n",
       "169                 Permira, TCV, Silver Lake Partners   欧盟  \n",
       "172  Amadeus Capital Partners, Atomico, Sequoia Cap...   欧盟  \n",
       "177  SoftBank Investment Advisers, NetEase, Amadeus...   欧盟  \n",
       "182  TPG, Ireland Strategic Investment Fund, Insigh...   欧盟  \n",
       "196           Volkswagen Group, Goldman Sachs, Seimens   欧盟  \n",
       "197  Amgen, IP Group Plc, Woodford Investment Manag...   欧盟  \n",
       "207  Mastercard Start Path, Balderton Capital, Trip...   欧盟  \n",
       "269                          SevenVentures, Bestseller   欧盟  \n",
       "290                              Didi Chuxing, Daimler   欧盟  \n",
       "297  Kevin Laws, Seaya Ventures, Rakuten Capital, I...   欧盟  \n",
       "317  Access Industries, Idinvest Partners, Kingdom ...   欧盟  \n",
       "320  Kerala Ventures, Accel, Bpifrance, Eurazeo, Ge...   欧盟  \n",
       "339  PROfounders Capital, Highland Europe , Fritz D...   欧盟  \n",
       "342    Lewis trust Group. Rocket Internet, Kinnevik AB   欧盟  \n",
       "349                                     Ginko Ventures   欧盟  \n",
       "396      Avenir Growth Capital, Eurazeo Prime Ventures   欧盟  \n",
       "411  Goldman Sachs Investment Partners, Kleiner Per...   欧盟  \n",
       "418                                    Mitsubishi Corp   欧盟  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "欧盟.insert(欧盟.shape[1], '地区分布', \"欧盟\", allow_duplicates=False)\n",
    "欧盟"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国家</th>\n",
       "      <th>行业</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <th>金融科技</th>\n",
       "      <td>1250</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>德国</th>\n",
       "      <th>电子商务</th>\n",
       "      <td>660</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">英国</th>\n",
       "      <th>电子商务</th>\n",
       "      <td>350</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>人工智能</th>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞典</th>\n",
       "      <th>金融科技</th>\n",
       "      <td>300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">德国</th>\n",
       "      <th>金融科技</th>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生命科学</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>法国</th>\n",
       "      <th>共享经济</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱尔兰</th>\n",
       "      <th>云计算</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞典</th>\n",
       "      <th>新能源</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">英国</th>\n",
       "      <th>游戏</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>物流</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>生命科学</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>马耳他</th>\n",
       "      <th>区块链</th>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>卢森堡</th>\n",
       "      <th>电子商务</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">法国</th>\n",
       "      <th>人工智能</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>健康科技</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>媒体和娱乐</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱沙尼亚</th>\n",
       "      <th>共享经济</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>芬兰</th>\n",
       "      <th>消费品</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <th>新能源</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>西班牙</th>\n",
       "      <th>共享经济</th>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            估值（亿人民币）  企业数量\n",
       "国家   行业                   \n",
       "英国   金融科技       1250     6\n",
       "德国   电子商务        660     5\n",
       "英国   电子商务        350     1\n",
       "     人工智能        300     2\n",
       "瑞典   金融科技        300     1\n",
       "德国   金融科技        200     1\n",
       "     生命科学        150     1\n",
       "法国   共享经济        150     1\n",
       "爱尔兰  云计算         150     1\n",
       "瑞典   新能源         150     1\n",
       "英国   游戏          150     1\n",
       "     物流          150     1\n",
       "     生命科学        150     1\n",
       "马耳他  区块链         150     1\n",
       "卢森堡  电子商务         70     1\n",
       "法国   人工智能         70     1\n",
       "     健康科技         70     1\n",
       "     媒体和娱乐        70     1\n",
       "爱沙尼亚 共享经济         70     1\n",
       "芬兰   消费品          70     1\n",
       "英国   新能源          70     1\n",
       "西班牙  共享经济         70     1"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 从估值、企业数量和行业分布进行统计\n",
    "欧盟[['国家','城市','企业名称','估值（亿人民币）','成立年份','行业']]\\\n",
    ".groupby(['国家','行业'])\\\n",
    ".agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    ".sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    ".rename ( columns = {\"企业名称\":\"企业数量\"} )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>行业</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2011</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>550</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>2012</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>370</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2015</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>350</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>英国</td>\n",
       "      <td>曼彻斯特</td>\n",
       "      <td>2004</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>350</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>2005</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>300</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>2013</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2013</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>德国</td>\n",
       "      <td>巴登符腾堡州</td>\n",
       "      <td>2000</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>德国</td>\n",
       "      <td>慕尼黑</td>\n",
       "      <td>2011</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>2006</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>爱尔兰</td>\n",
       "      <td>都柏林</td>\n",
       "      <td>2000</td>\n",
       "      <td>云计算</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>2016</td>\n",
       "      <td>新能源</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2012</td>\n",
       "      <td>游戏</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2012</td>\n",
       "      <td>物流</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2012</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>2013</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>2016</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>英国</td>\n",
       "      <td>牛津</td>\n",
       "      <td>2005</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>马耳他</td>\n",
       "      <td>-</td>\n",
       "      <td>2017</td>\n",
       "      <td>区块链</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>卢森堡</td>\n",
       "      <td>卢森堡</td>\n",
       "      <td>2014</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>2009</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>德国</td>\n",
       "      <td>汉堡</td>\n",
       "      <td>2014</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>2006</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>2013</td>\n",
       "      <td>健康科技</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>2016</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>爱沙尼亚</td>\n",
       "      <td>塔林</td>\n",
       "      <td>2013</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>芬兰</td>\n",
       "      <td>赫尔辛基</td>\n",
       "      <td>2016</td>\n",
       "      <td>消费品</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>2009</td>\n",
       "      <td>新能源</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>西班牙</td>\n",
       "      <td>马德里</td>\n",
       "      <td>2011</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      国家      城市  成立年份     行业  估值（亿人民币）  企业数量\n",
       "0     英国      伦敦  2011   金融科技       550     2\n",
       "1     德国      柏林  2012   电子商务       370     2\n",
       "2     英国      伦敦  2015   金融科技       350     2\n",
       "3     英国    曼彻斯特  2004   电子商务       350     1\n",
       "4     瑞典   斯德哥尔摩  2005   金融科技       300     1\n",
       "5     德国      柏林  2013   金融科技       200     1\n",
       "6     英国      伦敦  2013   金融科技       200     1\n",
       "7     德国  巴登符腾堡州  2000   生命科学       150     1\n",
       "8     德国     慕尼黑  2011   电子商务       150     1\n",
       "9     法国      巴黎  2006   共享经济       150     1\n",
       "10   爱尔兰     都柏林  2000    云计算       150     1\n",
       "11    瑞典   斯德哥尔摩  2016    新能源       150     1\n",
       "12    英国      伦敦  2012     游戏       150     1\n",
       "13    英国      伦敦  2012     物流       150     1\n",
       "14    英国      伦敦  2012   金融科技       150     1\n",
       "15    英国      伦敦  2013   人工智能       150     1\n",
       "16    英国   布里斯托尔  2016   人工智能       150     1\n",
       "17    英国      牛津  2005   生命科学       150     1\n",
       "18   马耳他       -  2017    区块链       150     1\n",
       "19   卢森堡     卢森堡  2014   电子商务        70     1\n",
       "20    德国      柏林  2009   电子商务        70     1\n",
       "21    德国      汉堡  2014   电子商务        70     1\n",
       "22    法国      巴黎  2006  媒体和娱乐        70     1\n",
       "23    法国      巴黎  2013   健康科技        70     1\n",
       "24    法国      巴黎  2016   人工智能        70     1\n",
       "25  爱沙尼亚      塔林  2013   共享经济        70     1\n",
       "26    芬兰    赫尔辛基  2016    消费品        70     1\n",
       "27    英国   布里斯托尔  2009    新能源        70     1\n",
       "28   西班牙     马德里  2011   共享经济        70     1"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 欧盟每年情况\n",
    "欧盟数据=欧盟[['国家','城市','企业名称','估值（亿人民币）','成立年份','行业']]\\\n",
    ".groupby(['国家','城市','成立年份','行业'])\\\n",
    ".agg({'估值（亿人民币）':\"sum\",'企业名称':'count'})\\\n",
    ".sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    ".rename(columns = {\"企业名称\":\"企业数量\"})\\\n",
    ".reset_index()\n",
    "欧盟数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"12\" halign=\"left\">估值（亿人民币）</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成立年份</th>\n",
       "      <th>2000</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2009</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国家</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>卢森堡</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>德国</th>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>法国</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>爱尔兰</th>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱沙尼亚</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞典</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>芬兰</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <td>NaN</td>\n",
       "      <td>350.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>550.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>350.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>西班牙</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>马耳他</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
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      "text/plain": [
       "     估值（亿人民币）                                                              \\\n",
       "成立年份     2000   2004   2005  2006  2009   2011   2012   2013  2014   2015   \n",
       "国家                                                                          \n",
       "卢森堡       NaN    NaN    NaN   NaN   NaN    NaN    NaN    NaN  70.0    NaN   \n",
       "德国      150.0    NaN    NaN   NaN  70.0  150.0  370.0  200.0  70.0    NaN   \n",
       "法国        NaN    NaN    NaN  70.0   NaN    NaN    NaN   70.0   NaN    NaN   \n",
       "爱尔兰     150.0    NaN    NaN   NaN   NaN    NaN    NaN    NaN   NaN    NaN   \n",
       "爱沙尼亚      NaN    NaN    NaN   NaN   NaN    NaN    NaN   70.0   NaN    NaN   \n",
       "瑞典        NaN    NaN  300.0   NaN   NaN    NaN    NaN    NaN   NaN    NaN   \n",
       "芬兰        NaN    NaN    NaN   NaN   NaN    NaN    NaN    NaN   NaN    NaN   \n",
       "英国        NaN  350.0  150.0   NaN  70.0  550.0  150.0  150.0   NaN  350.0   \n",
       "西班牙       NaN    NaN    NaN   NaN   NaN   70.0    NaN    NaN   NaN    NaN   \n",
       "马耳他       NaN    NaN    NaN   NaN   NaN    NaN    NaN    NaN   NaN    NaN   \n",
       "\n",
       "                    \n",
       "成立年份   2016   2017  \n",
       "国家                  \n",
       "卢森堡     NaN    NaN  \n",
       "德国      NaN    NaN  \n",
       "法国     70.0    NaN  \n",
       "爱尔兰     NaN    NaN  \n",
       "爱沙尼亚    NaN    NaN  \n",
       "瑞典    150.0    NaN  \n",
       "芬兰     70.0    NaN  \n",
       "英国    150.0    NaN  \n",
       "西班牙     NaN    NaN  \n",
       "马耳他     NaN  150.0  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 估值发展趋势\n",
    "欧盟估值数据_pivot=欧盟数据.groupby(['国家','城市','成立年份'])\\\n",
    ".agg({\"估值（亿人民币）\":\"sum\",\"估值（亿人民币）\":\"max\",\"估值（亿人民币）\":\"min\"})\\\n",
    ".reset_index()\\\n",
    ".pivot(index=\"国家\",columns=\"成立年份\", values=[\"估值（亿人民币）\"])\n",
    "欧盟估值数据_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
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       "        if (!display || display === 'none') {{\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "欧盟数据.iplot(kind=\"bar\", x=[\"国家\"], y=\"估值（亿人民币）\", asFigure=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 亚太地区分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>264</td>\n",
       "      <td>网易有道</td>\n",
       "      <td>Youdao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>周枫</td>\n",
       "      <td>2007</td>\n",
       "      <td>君联资本、慕华投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>222 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "6      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "10    11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "486  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "487  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "488  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "490  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "491  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构  \n",
       "序号                           \n",
       "0            春华资本、中投海外、红杉资本  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  \n",
       "6       摩根士丹利、中银集团、国泰君安（香港）  \n",
       "10              腾讯、华平投资、淡马锡  \n",
       "..                      ...  \n",
       "486          高瓴资本、晨兴资本、软银中国  \n",
       "487               君联资本、慕华投资  \n",
       "488          华平投资、红杉资本、经纬中国  \n",
       "490          顺为资本、达晨创投、华平投资  \n",
       "491                      腾讯  \n",
       "\n",
       "[222 rows x 10 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "亚太国家=[\"中国\",\"日本\",\"韩国\",\"朝鲜\",\"菲律宾\",\"马来西亚\",\"印度尼西亚\",\"新加坡\",\"澳大利亚\",\"新西兰\"]\n",
    "df.index.name=\"序号\"\n",
    "亚太=df[df['国家'].isin(亚太国家)]\n",
    "亚太"
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  {
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   "execution_count": 23,
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       "      <td>2</td>\n",
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       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
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       "      <td>张一鸣</td>\n",
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       "      <th>2</th>\n",
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       "      <td>滴滴出行</td>\n",
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       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "      <td>亚太地区</td>\n",
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       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
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       "      <th>10</th>\n",
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       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
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       "      <td>亚太地区</td>\n",
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       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
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       "      <th>490</th>\n",
       "      <td>264</td>\n",
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       "      <td>70</td>\n",
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       "      <td>上海</td>\n",
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       "      <td>264</td>\n",
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       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>亚太地区</td>\n",
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       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "6      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "10    11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "486  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "487  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "488  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "490  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "491  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构  地区分布  \n",
       "序号                                 \n",
       "0            春华资本、中投海外、红杉资本  亚太地区  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投  亚太地区  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  亚太地区  \n",
       "6       摩根士丹利、中银集团、国泰君安（香港）  亚太地区  \n",
       "10              腾讯、华平投资、淡马锡  亚太地区  \n",
       "..                      ...   ...  \n",
       "486          高瓴资本、晨兴资本、软银中国  亚太地区  \n",
       "487               君联资本、慕华投资  亚太地区  \n",
       "488          华平投资、红杉资本、经纬中国  亚太地区  \n",
       "490          顺为资本、达晨创投、华平投资  亚太地区  \n",
       "491                      腾讯  亚太地区  \n",
       "\n",
       "[222 rows x 11 columns]"
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     },
     "execution_count": 23,
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\"zerolinewidth\": 2}}}, \"title\": {\"font\": {\"color\": \"#151516\"}}, \"xaxis\": {\"gridcolor\": \"#F6F6F6\", \"showgrid\": true, \"tickfont\": {\"color\": \"#666666\"}, \"title\": {\"font\": {\"color\": \"#666666\"}, \"text\": \"\"}, \"zerolinecolor\": \"#F6F6F6\"}, \"yaxis\": {\"gridcolor\": \"#F6F6F6\", \"showgrid\": true, \"tickfont\": {\"color\": \"#666666\"}, \"title\": {\"font\": {\"color\": \"#666666\"}, \"text\": \"\"}, \"zerolinecolor\": \"#F6F6F6\"}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('2bf21a41-e80a-4ce5-ae67-1ed42ab8720d');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "亚太.iplot(kind=\"bar\", x=[\"国家\"], y=\"估值（亿人民币）\", asFigure=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 其它地区分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Infor</td>\n",
       "      <td>Infor</td>\n",
       "      <td>3500</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Jim Schaper</td>\n",
       "      <td>2002</td>\n",
       "      <td>Golden Gate Capital, Koch Equity Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>JUUL Labs</td>\n",
       "      <td>3400</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Adam Bowen, James Monsees, Kevin Burns, Tim Da...</td>\n",
       "      <td>2015</td>\n",
       "      <td>M13, Timothy Davis, Evolution VC Partners, Tig...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>爱彼迎</td>\n",
       "      <td>Airbnb</td>\n",
       "      <td>2700</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Brian Chesky, Joe Gebbia, Nathan Blecharczyk</td>\n",
       "      <td>2008</td>\n",
       "      <td>Tiger Global Management, Founders Fund, Y Comb...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>SpaceX</td>\n",
       "      <td>2500</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "      <td>Elon Musk</td>\n",
       "      <td>2002</td>\n",
       "      <td>DFJ, Founders Fund, Google, Bank of America, B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>WeWork</td>\n",
       "      <td>WeWork</td>\n",
       "      <td>2100</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Adam Neumann, Miguel McKevley</td>\n",
       "      <td>2010</td>\n",
       "      <td>Softbank, Hony Capital, Glade Brook Capital, W...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>264</td>\n",
       "      <td>VTS</td>\n",
       "      <td>VTS</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>房地产科技</td>\n",
       "      <td>Brandon Weber, Donald DeSantis, Karl Baum, Nia...</td>\n",
       "      <td>2012</td>\n",
       "      <td>Bessemer Venture Partners, Thrive Capital, Ope...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>264</td>\n",
       "      <td>WalkMe</td>\n",
       "      <td>WalkMe</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Dan Adika, Eyal Cohen, Rephael Sweary</td>\n",
       "      <td>2011</td>\n",
       "      <td>Gemini Israel Ventures, Scale Venture Partners...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>264</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>David A. Steinberg, John Sculley</td>\n",
       "      <td>2007</td>\n",
       "      <td>GPI Capital, GSO Capital Partners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>264</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>半月湾</td>\n",
       "      <td>物流</td>\n",
       "      <td>Keenan Wyrobek, Keller Rinaudo, Will Hetzler</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sequoia Capital, Visionnaire Ventures, Katalys...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>264</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd</td>\n",
       "      <td>2010</td>\n",
       "      <td>IVP (Institutional Venture Partners)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>218 rows × 10 columns</p>\n",
       "</div>"
      ],
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       "      排名                   企业名称           Company Name  估值（亿人民币）  国家   城市  \\\n",
       "序号                                                                          \n",
       "3      4                  Infor                  Infor      3500  美国   纽约   \n",
       "4      5              JUUL Labs              JUUL Labs      3400  美国  旧金山   \n",
       "5      6                    爱彼迎                 Airbnb      2700  美国  旧金山   \n",
       "7      8                 SpaceX                 SpaceX      2500  美国  洛杉矶   \n",
       "8      9                 WeWork                 WeWork      2100  美国   纽约   \n",
       "..   ...                    ...                    ...       ...  ..  ...   \n",
       "472  264                    VTS                    VTS        70  美国   纽约   \n",
       "474  264                 WalkMe                 WalkMe        70  美国  旧金山   \n",
       "489  264            Zeta Global            Zeta Global        70  美国   纽约   \n",
       "492  264  Zipline International  Zipline International        70  美国  半月湾   \n",
       "493  264           ZipRecruiter           ZipRecruiter        70  美国  洛杉矶   \n",
       "\n",
       "        行业                                            掌门人/创始人  成立年份  \\\n",
       "序号                                                                    \n",
       "3      云计算                                        Jim Schaper  2002   \n",
       "4      消费品  Adam Bowen, James Monsees, Kevin Burns, Tim Da...  2015   \n",
       "5     共享经济       Brian Chesky, Joe Gebbia, Nathan Blecharczyk  2008   \n",
       "7       航天                                          Elon Musk  2002   \n",
       "8     共享经济                      Adam Neumann, Miguel McKevley  2010   \n",
       "..     ...                                                ...   ...   \n",
       "472  房地产科技  Brandon Weber, Donald DeSantis, Karl Baum, Nia...  2012   \n",
       "474    云计算              Dan Adika, Eyal Cohen, Rephael Sweary  2011   \n",
       "489   人工智能                   David A. Steinberg, John Sculley  2007   \n",
       "492     物流       Keenan Wyrobek, Keller Rinaudo, Will Hetzler  2014   \n",
       "493   电子商务  Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd  2010   \n",
       "\n",
       "                                                部分投资机构  \n",
       "序号                                                      \n",
       "3         Golden Gate Capital, Koch Equity Development  \n",
       "4    M13, Timothy Davis, Evolution VC Partners, Tig...  \n",
       "5    Tiger Global Management, Founders Fund, Y Comb...  \n",
       "7    DFJ, Founders Fund, Google, Bank of America, B...  \n",
       "8    Softbank, Hony Capital, Glade Brook Capital, W...  \n",
       "..                                                 ...  \n",
       "472  Bessemer Venture Partners, Thrive Capital, Ope...  \n",
       "474  Gemini Israel Ventures, Scale Venture Partners...  \n",
       "489                  GPI Capital, GSO Capital Partners  \n",
       "492  Sequoia Capital, Visionnaire Ventures, Katalys...  \n",
       "493               IVP (Institutional Venture Partners)  \n",
       "\n",
       "[218 rows x 10 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "其它地区=[\"美国\",\"加拿大\",\"巴西\",\"以色列\",\"阿根廷\",\"爱沙尼亚\",\"西班牙\",\"新西兰\",\"哥伦比亚\"]\n",
    "df.index.name=\"序号\"\n",
    "其它=df[df['国家'].isin(其它地区)]\n",
    "其它"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>排名</th>\n",
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       "      <td>M13, Timothy Davis, Evolution VC Partners, Tig...</td>\n",
       "      <td>其它地区</td>\n",
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       "      <th>5</th>\n",
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       "      <td>爱彼迎</td>\n",
       "      <td>Airbnb</td>\n",
       "      <td>2700</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Brian Chesky, Joe Gebbia, Nathan Blecharczyk</td>\n",
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       "      <td>Tiger Global Management, Founders Fund, Y Comb...</td>\n",
       "      <td>其它地区</td>\n",
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       "      <th>7</th>\n",
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       "      <td>SpaceX</td>\n",
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       "      <td>2500</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>航天</td>\n",
       "      <td>Elon Musk</td>\n",
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       "      <td>DFJ, Founders Fund, Google, Bank of America, B...</td>\n",
       "      <td>其它地区</td>\n",
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       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>WeWork</td>\n",
       "      <td>WeWork</td>\n",
       "      <td>2100</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Adam Neumann, Miguel McKevley</td>\n",
       "      <td>2010</td>\n",
       "      <td>Softbank, Hony Capital, Glade Brook Capital, W...</td>\n",
       "      <td>其它地区</td>\n",
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       "      <td>VTS</td>\n",
       "      <td>VTS</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>房地产科技</td>\n",
       "      <td>Brandon Weber, Donald DeSantis, Karl Baum, Nia...</td>\n",
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       "      <td>其它地区</td>\n",
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       "      <td>264</td>\n",
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       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Dan Adika, Eyal Cohen, Rephael Sweary</td>\n",
       "      <td>2011</td>\n",
       "      <td>Gemini Israel Ventures, Scale Venture Partners...</td>\n",
       "      <td>其它地区</td>\n",
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       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>264</td>\n",
       "      <td>Zeta Global</td>\n",
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       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>David A. Steinberg, John Sculley</td>\n",
       "      <td>2007</td>\n",
       "      <td>GPI Capital, GSO Capital Partners</td>\n",
       "      <td>其它地区</td>\n",
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       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>264</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>半月湾</td>\n",
       "      <td>物流</td>\n",
       "      <td>Keenan Wyrobek, Keller Rinaudo, Will Hetzler</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sequoia Capital, Visionnaire Ventures, Katalys...</td>\n",
       "      <td>其它地区</td>\n",
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       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>264</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd</td>\n",
       "      <td>2010</td>\n",
       "      <td>IVP (Institutional Venture Partners)</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>218 rows × 11 columns</p>\n",
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      ],
      "text/plain": [
       "      排名                   企业名称           Company Name  估值（亿人民币）  国家   城市  \\\n",
       "序号                                                                          \n",
       "3      4                  Infor                  Infor      3500  美国   纽约   \n",
       "4      5              JUUL Labs              JUUL Labs      3400  美国  旧金山   \n",
       "5      6                    爱彼迎                 Airbnb      2700  美国  旧金山   \n",
       "7      8                 SpaceX                 SpaceX      2500  美国  洛杉矶   \n",
       "8      9                 WeWork                 WeWork      2100  美国   纽约   \n",
       "..   ...                    ...                    ...       ...  ..  ...   \n",
       "472  264                    VTS                    VTS        70  美国   纽约   \n",
       "474  264                 WalkMe                 WalkMe        70  美国  旧金山   \n",
       "489  264            Zeta Global            Zeta Global        70  美国   纽约   \n",
       "492  264  Zipline International  Zipline International        70  美国  半月湾   \n",
       "493  264           ZipRecruiter           ZipRecruiter        70  美国  洛杉矶   \n",
       "\n",
       "        行业                                            掌门人/创始人  成立年份  \\\n",
       "序号                                                                    \n",
       "3      云计算                                        Jim Schaper  2002   \n",
       "4      消费品  Adam Bowen, James Monsees, Kevin Burns, Tim Da...  2015   \n",
       "5     共享经济       Brian Chesky, Joe Gebbia, Nathan Blecharczyk  2008   \n",
       "7       航天                                          Elon Musk  2002   \n",
       "8     共享经济                      Adam Neumann, Miguel McKevley  2010   \n",
       "..     ...                                                ...   ...   \n",
       "472  房地产科技  Brandon Weber, Donald DeSantis, Karl Baum, Nia...  2012   \n",
       "474    云计算              Dan Adika, Eyal Cohen, Rephael Sweary  2011   \n",
       "489   人工智能                   David A. Steinberg, John Sculley  2007   \n",
       "492     物流       Keenan Wyrobek, Keller Rinaudo, Will Hetzler  2014   \n",
       "493   电子商务  Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd  2010   \n",
       "\n",
       "                                                部分投资机构  地区分布  \n",
       "序号                                                            \n",
       "3         Golden Gate Capital, Koch Equity Development  其它地区  \n",
       "4    M13, Timothy Davis, Evolution VC Partners, Tig...  其它地区  \n",
       "5    Tiger Global Management, Founders Fund, Y Comb...  其它地区  \n",
       "7    DFJ, Founders Fund, Google, Bank of America, B...  其它地区  \n",
       "8    Softbank, Hony Capital, Glade Brook Capital, W...  其它地区  \n",
       "..                                                 ...   ...  \n",
       "472  Bessemer Venture Partners, Thrive Capital, Ope...  其它地区  \n",
       "474  Gemini Israel Ventures, Scale Venture Partners...  其它地区  \n",
       "489                  GPI Capital, GSO Capital Partners  其它地区  \n",
       "492  Sequoia Capital, Visionnaire Ventures, Katalys...  其它地区  \n",
       "493               IVP (Institutional Venture Partners)  其它地区  \n",
       "\n",
       "[218 rows x 11 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "其它.insert(其它.shape[1], '地区分布', \"其它地区\", allow_duplicates=False)\n",
    "其它"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "其它.iplot(kind=\"bar\", x=[\"国家\"], y=\"估值（亿人民币）\", asFigure=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将欧盟、亚太和其它地区的数据整合在一起,进一步分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>排名</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>50</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>The Hut Group</td>\n",
       "      <td>350</td>\n",
       "      <td>英国</td>\n",
       "      <td>曼彻斯特</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>John Gallemore, Matthew Moulding</td>\n",
       "      <td>2004</td>\n",
       "      <td>Artemis, Lewis Trust Group, Kohlberg Kravis Ro...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>57</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>Auto1 Group</td>\n",
       "      <td>300</td>\n",
       "      <td>德国</td>\n",
       "      <td>柏林</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Christian Bertermann, Hakan Koc</td>\n",
       "      <td>2012</td>\n",
       "      <td>DN Capital, Piton Capital, DST Global, Princev...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>57</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>Klarna</td>\n",
       "      <td>300</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Niklas Adalberth, Sebastian Siemiatkowski, Vic...</td>\n",
       "      <td>2005</td>\n",
       "      <td>Investment AB Öresund, Sequoia Capital, Genera...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>57</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>TransferWise</td>\n",
       "      <td>300</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Kristo Kaarmann, Taavet Hinrikus</td>\n",
       "      <td>2011</td>\n",
       "      <td>Seedcamp, IA Ventures , Valar Ventures, Index ...</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>83</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>Greensill</td>\n",
       "      <td>250</td>\n",
       "      <td>英国</td>\n",
       "      <td>伦敦</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jason Austin, Lex Greensill</td>\n",
       "      <td>2011</td>\n",
       "      <td>General Atlantic, SoftBank Investment Advisers</td>\n",
       "      <td>欧盟</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>264</td>\n",
       "      <td>VTS</td>\n",
       "      <td>VTS</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>房地产科技</td>\n",
       "      <td>Brandon Weber, Donald DeSantis, Karl Baum, Nia...</td>\n",
       "      <td>2012</td>\n",
       "      <td>Bessemer Venture Partners, Thrive Capital, Ope...</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>264</td>\n",
       "      <td>WalkMe</td>\n",
       "      <td>WalkMe</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Dan Adika, Eyal Cohen, Rephael Sweary</td>\n",
       "      <td>2011</td>\n",
       "      <td>Gemini Israel Ventures, Scale Venture Partners...</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>264</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>Zeta Global</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>纽约</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>David A. Steinberg, John Sculley</td>\n",
       "      <td>2007</td>\n",
       "      <td>GPI Capital, GSO Capital Partners</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>264</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>Zipline International</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>半月湾</td>\n",
       "      <td>物流</td>\n",
       "      <td>Keenan Wyrobek, Keller Rinaudo, Will Hetzler</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sequoia Capital, Visionnaire Ventures, Katalys...</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>264</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd</td>\n",
       "      <td>2010</td>\n",
       "      <td>IVP (Institutional Venture Partners)</td>\n",
       "      <td>其它地区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>472 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名                   企业名称           Company Name  估值（亿人民币）  国家     城市  \\\n",
       "序号                                                                            \n",
       "55    50          The Hut Group          The Hut Group       350  英国   曼彻斯特   \n",
       "56    57            Auto1 Group            Auto1 Group       300  德国     柏林   \n",
       "62    57                 Klarna                 Klarna       300  瑞典  斯德哥尔摩   \n",
       "73    57           TransferWise           TransferWise       300  英国     伦敦   \n",
       "82    83              Greensill              Greensill       250  英国     伦敦   \n",
       "..   ...                    ...                    ...       ...  ..    ...   \n",
       "472  264                    VTS                    VTS        70  美国     纽约   \n",
       "474  264                 WalkMe                 WalkMe        70  美国    旧金山   \n",
       "489  264            Zeta Global            Zeta Global        70  美国     纽约   \n",
       "492  264  Zipline International  Zipline International        70  美国    半月湾   \n",
       "493  264           ZipRecruiter           ZipRecruiter        70  美国    洛杉矶   \n",
       "\n",
       "        行业                                            掌门人/创始人  成立年份  \\\n",
       "序号                                                                    \n",
       "55    电子商务                   John Gallemore, Matthew Moulding  2004   \n",
       "56    电子商务                    Christian Bertermann, Hakan Koc  2012   \n",
       "62    金融科技  Niklas Adalberth, Sebastian Siemiatkowski, Vic...  2005   \n",
       "73    金融科技                   Kristo Kaarmann, Taavet Hinrikus  2011   \n",
       "82    金融科技                        Jason Austin, Lex Greensill  2011   \n",
       "..     ...                                                ...   ...   \n",
       "472  房地产科技  Brandon Weber, Donald DeSantis, Karl Baum, Nia...  2012   \n",
       "474    云计算              Dan Adika, Eyal Cohen, Rephael Sweary  2011   \n",
       "489   人工智能                   David A. Steinberg, John Sculley  2007   \n",
       "492     物流       Keenan Wyrobek, Keller Rinaudo, Will Hetzler  2014   \n",
       "493   电子商务  Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd  2010   \n",
       "\n",
       "                                                部分投资机构  地区分布  \n",
       "序号                                                            \n",
       "55   Artemis, Lewis Trust Group, Kohlberg Kravis Ro...    欧盟  \n",
       "56   DN Capital, Piton Capital, DST Global, Princev...    欧盟  \n",
       "62   Investment AB Öresund, Sequoia Capital, Genera...    欧盟  \n",
       "73   Seedcamp, IA Ventures , Valar Ventures, Index ...    欧盟  \n",
       "82      General Atlantic, SoftBank Investment Advisers    欧盟  \n",
       "..                                                 ...   ...  \n",
       "472  Bessemer Venture Partners, Thrive Capital, Ope...  其它地区  \n",
       "474  Gemini Israel Ventures, Scale Venture Partners...  其它地区  \n",
       "489                  GPI Capital, GSO Capital Partners  其它地区  \n",
       "492  Sequoia Capital, Visionnaire Ventures, Katalys...  其它地区  \n",
       "493               IVP (Institutional Venture Partners)  其它地区  \n",
       "\n",
       "[472 rows x 11 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "分类处理数据=pd.concat([欧盟,亚太,其它])\n",
    "分类处理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将数据整合成函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def place(i):\n",
    "    place_list =[\"欧盟\",\"亚太地区\",\"其它地区\"]\n",
    "    if i in place_list:\n",
    "        place_choose=分类处理数据[分类处理数据['地区分布'].isin([i])]\n",
    "        return place_choose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "      <th>地区分布</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>序号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>字节跳动</td>\n",
       "      <td>Bytedance</td>\n",
       "      <td>5000</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>张一鸣</td>\n",
       "      <td>2012</td>\n",
       "      <td>红杉资本、海纳亚洲、纪源资本、启明创投</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>滴滴出行</td>\n",
       "      <td>Didi Chuxing</td>\n",
       "      <td>3600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>程维</td>\n",
       "      <td>2012</td>\n",
       "      <td>腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>陆金所</td>\n",
       "      <td>Lufax</td>\n",
       "      <td>2700</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>计葵生</td>\n",
       "      <td>2011</td>\n",
       "      <td>摩根士丹利、中银集团、国泰君安（香港）</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>264</td>\n",
       "      <td>有利网</td>\n",
       "      <td>Yooli</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>吴逸然</td>\n",
       "      <td>2012</td>\n",
       "      <td>高瓴资本、晨兴资本、软银中国</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>264</td>\n",
       "      <td>网易有道</td>\n",
       "      <td>Youdao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>周枫</td>\n",
       "      <td>2007</td>\n",
       "      <td>君联资本、慕华投资</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>264</td>\n",
       "      <td>云鸟科技</td>\n",
       "      <td>Yunniao</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>物流</td>\n",
       "      <td>韩毅</td>\n",
       "      <td>2014</td>\n",
       "      <td>华平投资、红杉资本、经纬中国</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>264</td>\n",
       "      <td>掌门1对1</td>\n",
       "      <td>Zhangmen</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>张翼</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、达晨创投、华平投资</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>亚太地区</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>222 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名   企业名称   Company Name  估值（亿人民币）  国家  城市     行业 掌门人/创始人  成立年份  \\\n",
       "序号                                                                      \n",
       "0      1   蚂蚁金服  Ant Financial     10000  中国  杭州   金融科技     井贤栋  2014   \n",
       "1      2   字节跳动      Bytedance      5000  中国  北京  媒体和娱乐     张一鸣  2012   \n",
       "2      3   滴滴出行   Didi Chuxing      3600  中国  北京   共享经济      程维  2012   \n",
       "6      6    陆金所          Lufax      2700  中国  上海   金融科技     计葵生  2011   \n",
       "10    11   微众银行         WeBank      1500  中国  深圳   金融科技      顾敏  2014   \n",
       "..   ...    ...            ...       ...  ..  ..    ...     ...   ...   \n",
       "486  264    有利网          Yooli        70  中国  北京   金融科技     吴逸然  2012   \n",
       "487  264   网易有道         Youdao        70  中国  北京  软件与服务      周枫  2007   \n",
       "488  264   云鸟科技        Yunniao        70  中国  北京     物流      韩毅  2014   \n",
       "490  264  掌门1对1       Zhangmen        70  中国  上海   教育科技      张翼  2014   \n",
       "491  264     转转     Zhuanzhuan        70  中国  北京   电子商务     姚劲波  2015   \n",
       "\n",
       "                     部分投资机构  地区分布  \n",
       "序号                                 \n",
       "0            春华资本、中投海外、红杉资本  亚太地区  \n",
       "1       红杉资本、海纳亚洲、纪源资本、启明创投  亚太地区  \n",
       "2    腾讯、阿里巴巴、红杉资本、经纬中国、纪源资本  亚太地区  \n",
       "6       摩根士丹利、中银集团、国泰君安（香港）  亚太地区  \n",
       "10              腾讯、华平投资、淡马锡  亚太地区  \n",
       "..                      ...   ...  \n",
       "486          高瓴资本、晨兴资本、软银中国  亚太地区  \n",
       "487               君联资本、慕华投资  亚太地区  \n",
       "488          华平投资、红杉资本、经纬中国  亚太地区  \n",
       "490          顺为资本、达晨创投、华平投资  亚太地区  \n",
       "491                      腾讯  亚太地区  \n",
       "\n",
       "[222 rows x 11 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "地区选择=place('亚太地区')\n",
    "地区选择"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
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       "      <th></th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>企业数量</th>\n",
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       "  </thead>\n",
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       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>2300</td>\n",
       "      <td>13</td>\n",
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       "    <tr>\n",
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       "      <td>北京</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>1430</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>上海</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>780</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>1920</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>北京</td>\n",
       "      <td>媒体和娱乐</td>\n",
       "      <td>6890</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>电子商务</td>\n",
       "      <td>350</td>\n",
       "      <td>1</td>\n",
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       "      <th>97</th>\n",
       "      <td>杭州</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>马卡迪</td>\n",
       "      <td>房地产科技</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
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       "<p>99 rows × 4 columns</p>\n",
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       "     城市     行业  估值（亿人民币）  企业数量\n",
       "0    北京   电子商务      2300    13\n",
       "1    北京   人工智能      1430     9\n",
       "2    上海   电子商务       780     8\n",
       "3    北京   金融科技      1920     8\n",
       "4    北京  媒体和娱乐      6890     7\n",
       "..  ...    ...       ...   ...\n",
       "94  新加坡   共享经济      1000     1\n",
       "95  新加坡   电子商务       350     1\n",
       "96   无锡    大数据        70     1\n",
       "97   杭州   人工智能       100     1\n",
       "98  马卡迪  房地产科技        70     1\n",
       "\n",
       "[99 rows x 4 columns]"
      ]
     },
     "execution_count": 29,
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   ],
   "source": [
    "# 从估值、企业数量和行业分布进行统计\n",
    "地区行业数据=地区选择[['城市','企业名称','估值（亿人民币）','成立年份','行业','地区分布']]\\\n",
    ".groupby(['城市','行业'])\\\n",
    ".agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    ".sort_values(['企业名称'],ascending=False)\\\n",
    ".rename (columns = {\"企业名称\":\"企业数量\"} )\\\n",
    ".reset_index()\n",
    "地区行业数据"
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       "                            \n",
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       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "地区行业数据.iplot(kind=\"bar\", x=[\"行业\"], y=\"估值（亿人民币）\", asFigure=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据分析\n",
    "在地区选择的函数选择下，可以有三种地区选择，分别是欧盟、亚太和其他地区。  \n",
    "选择任一地区进行数据分类聚合，形成新的数据表格。  \n",
    "将分析筛选后的数据进行画图，展现该地区内的独角兽企业在行业内估值发展状况。  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据分析三、国家行业年份筛选器"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 取出所有国家做成列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['中国', '美国', '新加坡', '印度尼西亚', '印度', '韩国', '瑞士', '英国', '德国', '瑞典',\n",
       "       '巴西', '澳大利亚', '马耳他', '法国', '以色列', '爱尔兰', '日本', '阿根廷', '爱沙尼亚',\n",
       "       '西班牙', '卢森堡', '芬兰', '哥伦比亚', '菲律宾'], dtype=object)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "国家=pd.unique(df['国家'])\n",
    "国家"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['哥伦比亚',\n",
       " '瑞士',\n",
       " '爱尔兰',\n",
       " '以色列',\n",
       " '美国',\n",
       " '德国',\n",
       " '澳大利亚',\n",
       " '爱沙尼亚',\n",
       " '西班牙',\n",
       " '菲律宾',\n",
       " '瑞典',\n",
       " '卢森堡',\n",
       " '阿根廷',\n",
       " '芬兰',\n",
       " '新加坡',\n",
       " '中国',\n",
       " '印度',\n",
       " '马耳他',\n",
       " '日本',\n",
       " '英国',\n",
       " '法国',\n",
       " '印度尼西亚',\n",
       " '韩国',\n",
       " '巴西']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country_list =list(set(国家))\n",
    "country_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(country_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>138</td>\n",
       "      <td>Infinidat</td>\n",
       "      <td>Infinidat</td>\n",
       "      <td>150</td>\n",
       "      <td>以色列</td>\n",
       "      <td>特拉维夫</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Moshe Yanai</td>\n",
       "      <td>2011</td>\n",
       "      <td>TPG Growth, Goldman Sachs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>138</td>\n",
       "      <td>Landa Digital Printing</td>\n",
       "      <td>Landa Digital Printing</td>\n",
       "      <td>150</td>\n",
       "      <td>以色列</td>\n",
       "      <td>雷霍沃特</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>Benny Landa</td>\n",
       "      <td>2002</td>\n",
       "      <td>Skion, GmBH, Altana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>138</td>\n",
       "      <td>Monday.com</td>\n",
       "      <td>Monday.com</td>\n",
       "      <td>150</td>\n",
       "      <td>以色列</td>\n",
       "      <td>特拉维夫</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Eran Zinman, Roy Mann</td>\n",
       "      <td>2012</td>\n",
       "      <td>Entrée Capital, Genesis Partners, Insight Part...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>264</td>\n",
       "      <td>Como</td>\n",
       "      <td>Como</td>\n",
       "      <td>70</td>\n",
       "      <td>以色列</td>\n",
       "      <td>耐斯兹敖那</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Dror Erez, Gaby Bilczyk, Ronen Shilo</td>\n",
       "      <td>2010</td>\n",
       "      <td>JP Morgan partners, Benchmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>264</td>\n",
       "      <td>ironSource</td>\n",
       "      <td>ironSource</td>\n",
       "      <td>70</td>\n",
       "      <td>以色列</td>\n",
       "      <td>特拉维夫</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Arnon Harish, Eyal Milrad, Gil Shoham, Itay Mi...</td>\n",
       "      <td>2010</td>\n",
       "      <td>Saban Capital Group, Access Industries</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>264</td>\n",
       "      <td>Lightricks</td>\n",
       "      <td>Lightricks</td>\n",
       "      <td>70</td>\n",
       "      <td>以色列</td>\n",
       "      <td>耶路撒冷</td>\n",
       "      <td>云计算</td>\n",
       "      <td>Amit Goldstein, Itai Tsiddon, Nir Pochter, Yar...</td>\n",
       "      <td>2013</td>\n",
       "      <td>Viola Ventures, Insight Partners, Goldman Sach...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>264</td>\n",
       "      <td>OrCam Technologies</td>\n",
       "      <td>OrCam Technologies</td>\n",
       "      <td>70</td>\n",
       "      <td>以色列</td>\n",
       "      <td>耶路撒冷</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Amnon Shashua, Ziv Aviram</td>\n",
       "      <td>2010</td>\n",
       "      <td>Clal Insurance Enterprises Holdings , Meitav I...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名                    企业名称            Company Name  估值（亿人民币）   国家  \\\n",
       "178  138               Infinidat               Infinidat       150  以色列   \n",
       "184  138  Landa Digital Printing  Landa Digital Printing       150  以色列   \n",
       "190  138              Monday.com              Monday.com       150  以色列   \n",
       "310  264                    Como                    Como        70  以色列   \n",
       "364  264              ironSource              ironSource        70  以色列   \n",
       "384  264              Lightricks              Lightricks        70  以色列   \n",
       "415  264      OrCam Technologies      OrCam Technologies        70  以色列   \n",
       "\n",
       "        城市     行业                                            掌门人/创始人  成立年份  \\\n",
       "178   特拉维夫    云计算                                        Moshe Yanai  2011   \n",
       "184   雷霍沃特  软件与服务                                        Benny Landa  2002   \n",
       "190   特拉维夫    云计算                              Eran Zinman, Roy Mann  2012   \n",
       "310  耐斯兹敖那    云计算               Dror Erez, Gaby Bilczyk, Ronen Shilo  2010   \n",
       "364   特拉维夫   生命科学  Arnon Harish, Eyal Milrad, Gil Shoham, Itay Mi...  2010   \n",
       "384   耶路撒冷    云计算  Amit Goldstein, Itai Tsiddon, Nir Pochter, Yar...  2013   \n",
       "415   耶路撒冷   人工智能                          Amnon Shashua, Ziv Aviram  2010   \n",
       "\n",
       "                                                部分投资机构  \n",
       "178                          TPG Growth, Goldman Sachs  \n",
       "184                                Skion, GmBH, Altana  \n",
       "190  Entrée Capital, Genesis Partners, Insight Part...  \n",
       "310                      JP Morgan partners, Benchmark  \n",
       "364             Saban Capital Group, Access Industries  \n",
       "384  Viola Ventures, Insight Partners, Goldman Sach...  \n",
       "415  Clal Insurance Enterprises Holdings , Meitav I...  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['国家'].isin(['以色列'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def country(i):\n",
    "    国家=pd.unique(df['国家'])\n",
    "    country_list =list(set(国家))\n",
    "    if i in country_list:\n",
    "        country_choose=df[df['国家'].isin([i])]\n",
    "        return country_choose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>Paytm</td>\n",
       "      <td>Paytm</td>\n",
       "      <td>700</td>\n",
       "      <td>印度</td>\n",
       "      <td>诺伊达</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Vijay Shekhar Sharma</td>\n",
       "      <td>2010</td>\n",
       "      <td>Alibaba Group, SoftBank, Berkshire Hathaway, S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>BYJU’s</td>\n",
       "      <td>BYJU’s</td>\n",
       "      <td>400</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>教育科技</td>\n",
       "      <td>Byju Raveendran, Divya Gokulnath</td>\n",
       "      <td>2008</td>\n",
       "      <td>Aarin Capital, Sequoia Capital India, Chan Zuc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>43</td>\n",
       "      <td>Ola Cabs</td>\n",
       "      <td>Ola Cabs</td>\n",
       "      <td>400</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Ankit Bhati, Bhavish Aggarwal</td>\n",
       "      <td>2010</td>\n",
       "      <td>Tiger Global Management, Hyundai Motor Company...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>50</td>\n",
       "      <td>OYO Rooms</td>\n",
       "      <td>OYO Rooms</td>\n",
       "      <td>350</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Ritesh Agarwal</td>\n",
       "      <td>2013</td>\n",
       "      <td>Greenoaks Capital, SoftBank, SoftBank Investme...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>57</td>\n",
       "      <td>Zomato</td>\n",
       "      <td>Zomato</td>\n",
       "      <td>300</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>物流</td>\n",
       "      <td>Deepinder Goyal, Pankaj Chaddah</td>\n",
       "      <td>2008</td>\n",
       "      <td>Info Edge, Sequoia Capital, Vy Capital, Temase...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>84</td>\n",
       "      <td>Paytm Mall</td>\n",
       "      <td>Paytm Mall</td>\n",
       "      <td>200</td>\n",
       "      <td>印度</td>\n",
       "      <td>诺伊达</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Vijay Shekhar Sharma</td>\n",
       "      <td>2010</td>\n",
       "      <td>SoftBank, Alibaba Group</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>84</td>\n",
       "      <td>Swiggy</td>\n",
       "      <td>Swiggy</td>\n",
       "      <td>200</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>物流</td>\n",
       "      <td>Nandan Reddy, Rahul Jaimini, Sriharsha Majety</td>\n",
       "      <td>2014</td>\n",
       "      <td>DST Global, Naspers, Bessemer Venture Partners...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>138</td>\n",
       "      <td>BillDesk</td>\n",
       "      <td>BillDesk</td>\n",
       "      <td>150</td>\n",
       "      <td>印度</td>\n",
       "      <td>艾哈迈达巴德</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Karthik Ganapathy, Ajay Kaushal, MN Srinivasu</td>\n",
       "      <td>2000</td>\n",
       "      <td>Visa, General Atlantic, TA Associates, Clearst...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>138</td>\n",
       "      <td>Delhivery</td>\n",
       "      <td>Delhivery</td>\n",
       "      <td>150</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>物流</td>\n",
       "      <td>Bhavesh Manglani, Kapil Bharati, Mohit Tandon,...</td>\n",
       "      <td>2011</td>\n",
       "      <td>Nexus Venture Partners, Multiples Alternate As...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>138</td>\n",
       "      <td>Mu Sigma</td>\n",
       "      <td>Mu Sigma</td>\n",
       "      <td>150</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>大数据</td>\n",
       "      <td>Dhiraj C Rajaram</td>\n",
       "      <td>2004</td>\n",
       "      <td>Sequoia Capital India, General Atlantic, Maste...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>138</td>\n",
       "      <td>ReNew Power</td>\n",
       "      <td>ReNew Power</td>\n",
       "      <td>150</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Sumant Sinha</td>\n",
       "      <td>2011</td>\n",
       "      <td>Goldman Sachs, Abu Dhabi Investment Authority,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287</th>\n",
       "      <td>264</td>\n",
       "      <td>BigBasket</td>\n",
       "      <td>BigBasket</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>新零售</td>\n",
       "      <td>Abhinay Choudhari, Hari Menon, Vipul Parekh, V...</td>\n",
       "      <td>2011</td>\n",
       "      <td>Mirae Asset-Naver Asia Growth Fund, Alibaba Gr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>323</th>\n",
       "      <td>264</td>\n",
       "      <td>Dream11</td>\n",
       "      <td>Dream11</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>孟买</td>\n",
       "      <td>游戏</td>\n",
       "      <td>Harsh Jain</td>\n",
       "      <td>2012</td>\n",
       "      <td>Tencent Holdings, Steadview Capital</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>347</th>\n",
       "      <td>264</td>\n",
       "      <td>Hike</td>\n",
       "      <td>Hike</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>新德里</td>\n",
       "      <td>即时通讯</td>\n",
       "      <td>Kavin Bharti Mittal</td>\n",
       "      <td>2012</td>\n",
       "      <td>Foxconn Technology Group, Tencent Holdings, Bh...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>264</td>\n",
       "      <td>InMobi</td>\n",
       "      <td>InMobi</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>软件与服务</td>\n",
       "      <td>Abhay Singhal, Amit Gupta, Mohit Saxena, Navee...</td>\n",
       "      <td>2007</td>\n",
       "      <td>Softbank Capital, Kleiner Perkins, Sherpalo Ve...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>264</td>\n",
       "      <td>Ola Electric</td>\n",
       "      <td>Ola Electric</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>Anand Shah, Ankit Jain</td>\n",
       "      <td>2017</td>\n",
       "      <td>Matrix Partners India, Tata Sons Ltd, SoftBank...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>264</td>\n",
       "      <td>PolicyBazaar</td>\n",
       "      <td>PolicyBazaar</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Alok Bansal, Yashish Dahiya</td>\n",
       "      <td>2008</td>\n",
       "      <td>SoftBank Investment Advisors, Wellington Manag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>264</td>\n",
       "      <td>Quikr</td>\n",
       "      <td>Quikr</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Pranay Chulet, Jiby Thomas</td>\n",
       "      <td>2008</td>\n",
       "      <td>Trifecta Capital Advisors, Tiger Global Manage...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>264</td>\n",
       "      <td>Rivigo</td>\n",
       "      <td>Rivigo</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>物流</td>\n",
       "      <td>Deepak Garg, Gazal Kalra</td>\n",
       "      <td>2014</td>\n",
       "      <td>SAIF Partners, Warburg Pincus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>264</td>\n",
       "      <td>Shopclues</td>\n",
       "      <td>Shopclues</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>古尔冈</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Radhika Aggarwal, Sandeep Aggarwal, Sanjay Sethi</td>\n",
       "      <td>2011</td>\n",
       "      <td>GIC, Tiger Global Management, Nexus Venture Pa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>264</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Amod Malviya, Sujeet kumar, Vaibhav Gupta</td>\n",
       "      <td>2016</td>\n",
       "      <td>Lightspeed Venture Partners, DST Global</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名          企业名称  Company Name  估值（亿人民币）  国家      城市     行业  \\\n",
       "23    23         Paytm         Paytm       700  印度     诺伊达   金融科技   \n",
       "42    43        BYJU’s        BYJU’s       400  印度    班加罗尔   教育科技   \n",
       "45    43      Ola Cabs      Ola Cabs       400  印度    班加罗尔   共享经济   \n",
       "52    50     OYO Rooms     OYO Rooms       350  印度     古尔冈   共享经济   \n",
       "81    57        Zomato        Zomato       300  印度     古尔冈     物流   \n",
       "113   84    Paytm Mall    Paytm Mall       200  印度     诺伊达   电子商务   \n",
       "123   84        Swiggy        Swiggy       200  印度    班加罗尔     物流   \n",
       "146  138      BillDesk      BillDesk       150  印度  艾哈迈达巴德   金融科技   \n",
       "163  138     Delhivery     Delhivery       150  印度     古尔冈     物流   \n",
       "192  138      Mu Sigma      Mu Sigma       150  印度    班加罗尔    大数据   \n",
       "206  138   ReNew Power   ReNew Power       150  印度     古尔冈    新能源   \n",
       "287  264     BigBasket     BigBasket        70  印度    班加罗尔    新零售   \n",
       "323  264       Dream11       Dream11        70  印度      孟买     游戏   \n",
       "347  264          Hike          Hike        70  印度     新德里   即时通讯   \n",
       "361  264        InMobi        InMobi        70  印度    班加罗尔  软件与服务   \n",
       "410  264  Ola Electric  Ola Electric        70  印度    班加罗尔   共享经济   \n",
       "422  264  PolicyBazaar  PolicyBazaar        70  印度     古尔冈   金融科技   \n",
       "425  264         Quikr         Quikr        70  印度    班加罗尔   电子商务   \n",
       "432  264        Rivigo        Rivigo        70  印度     古尔冈     物流   \n",
       "437  264     Shopclues     Shopclues        70  印度     古尔冈   电子商务   \n",
       "465  264         Udaan         Udaan        70  印度    班加罗尔   电子商务   \n",
       "\n",
       "                                               掌门人/创始人  成立年份  \\\n",
       "23                                Vijay Shekhar Sharma  2010   \n",
       "42                    Byju Raveendran, Divya Gokulnath  2008   \n",
       "45                       Ankit Bhati, Bhavish Aggarwal  2010   \n",
       "52                                      Ritesh Agarwal  2013   \n",
       "81                     Deepinder Goyal, Pankaj Chaddah  2008   \n",
       "113                               Vijay Shekhar Sharma  2010   \n",
       "123      Nandan Reddy, Rahul Jaimini, Sriharsha Majety  2014   \n",
       "146      Karthik Ganapathy, Ajay Kaushal, MN Srinivasu  2000   \n",
       "163  Bhavesh Manglani, Kapil Bharati, Mohit Tandon,...  2011   \n",
       "192                                   Dhiraj C Rajaram  2004   \n",
       "206                                       Sumant Sinha  2011   \n",
       "287  Abhinay Choudhari, Hari Menon, Vipul Parekh, V...  2011   \n",
       "323                                         Harsh Jain  2012   \n",
       "347                                Kavin Bharti Mittal  2012   \n",
       "361  Abhay Singhal, Amit Gupta, Mohit Saxena, Navee...  2007   \n",
       "410                             Anand Shah, Ankit Jain  2017   \n",
       "422                        Alok Bansal, Yashish Dahiya  2008   \n",
       "425                         Pranay Chulet, Jiby Thomas  2008   \n",
       "432                           Deepak Garg, Gazal Kalra  2014   \n",
       "437   Radhika Aggarwal, Sandeep Aggarwal, Sanjay Sethi  2011   \n",
       "465          Amod Malviya, Sujeet kumar, Vaibhav Gupta  2016   \n",
       "\n",
       "                                                部分投资机构  \n",
       "23   Alibaba Group, SoftBank, Berkshire Hathaway, S...  \n",
       "42   Aarin Capital, Sequoia Capital India, Chan Zuc...  \n",
       "45   Tiger Global Management, Hyundai Motor Company...  \n",
       "52   Greenoaks Capital, SoftBank, SoftBank Investme...  \n",
       "81   Info Edge, Sequoia Capital, Vy Capital, Temase...  \n",
       "113                            SoftBank, Alibaba Group  \n",
       "123  DST Global, Naspers, Bessemer Venture Partners...  \n",
       "146  Visa, General Atlantic, TA Associates, Clearst...  \n",
       "163  Nexus Venture Partners, Multiples Alternate As...  \n",
       "192  Sequoia Capital India, General Atlantic, Maste...  \n",
       "206  Goldman Sachs, Abu Dhabi Investment Authority,...  \n",
       "287  Mirae Asset-Naver Asia Growth Fund, Alibaba Gr...  \n",
       "323                Tencent Holdings, Steadview Capital  \n",
       "347  Foxconn Technology Group, Tencent Holdings, Bh...  \n",
       "361  Softbank Capital, Kleiner Perkins, Sherpalo Ve...  \n",
       "410  Matrix Partners India, Tata Sons Ltd, SoftBank...  \n",
       "422  SoftBank Investment Advisors, Wellington Manag...  \n",
       "425  Trifecta Capital Advisors, Tiger Global Manage...  \n",
       "432                      SAIF Partners, Warburg Pincus  \n",
       "437  GIC, Tiger Global Management, Nexus Venture Pa...  \n",
       "465            Lightspeed Venture Partners, DST Global  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country(\"印度\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 取出所有行业做成列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['游戏',\n",
       " '媒体和娱乐',\n",
       " '人工智能',\n",
       " '新零售',\n",
       " '航天',\n",
       " '大数据',\n",
       " '消费品',\n",
       " '生命科学',\n",
       " '物流',\n",
       " '机器人',\n",
       " '房地产科技',\n",
       " '区块链',\n",
       " '金融科技',\n",
       " '教育科技',\n",
       " '新能源汽车',\n",
       " '健康科技',\n",
       " '网络安全',\n",
       " '电子商务',\n",
       " '虚拟与增强现实',\n",
       " '即时通讯',\n",
       " '共享经济',\n",
       " '云计算',\n",
       " '软件与服务',\n",
       " '3D印刷',\n",
       " '新能源']"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "行业=pd.unique(df['行业'])\n",
    "industry_list =list(set(行业))\n",
    "industry_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def industry(i):\n",
    "    行业=pd.unique(df['行业'])\n",
    "    industry_list =list(set(行业))\n",
    "    if i in industry_list:\n",
    "        industry_choose=df[df['行业'].isin([i])]\n",
    "        return industry_choose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>车好多</td>\n",
       "      <td>CARS</td>\n",
       "      <td>600</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>杨浩涌</td>\n",
       "      <td>2011</td>\n",
       "      <td>红杉资本、今日资本、IDG、经纬中国</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>25</td>\n",
       "      <td>Coupang</td>\n",
       "      <td>Coupang</td>\n",
       "      <td>600</td>\n",
       "      <td>韩国</td>\n",
       "      <td>首尔</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Bom Kim</td>\n",
       "      <td>2010</td>\n",
       "      <td>SoftBank Investment Advisers, Altos Ventures, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>25</td>\n",
       "      <td>Wish</td>\n",
       "      <td>Wish</td>\n",
       "      <td>600</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Danny Zhang, Peter Szulczewski</td>\n",
       "      <td>2010</td>\n",
       "      <td>Formation 8, GGV Capital, Founders Fund, DST G...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34</td>\n",
       "      <td>美菜网</td>\n",
       "      <td>Meicai</td>\n",
       "      <td>500</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>刘传军</td>\n",
       "      <td>2014</td>\n",
       "      <td>顺为资本、纪源资本、真格基金</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>34</td>\n",
       "      <td>Tokopedia</td>\n",
       "      <td>Tokopedia</td>\n",
       "      <td>500</td>\n",
       "      <td>印度尼西亚</td>\n",
       "      <td>雅加达</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Leontinus Alpha Edison, William Tanuwijaya</td>\n",
       "      <td>2009</td>\n",
       "      <td>Indonusa Dwitama, East Ventures, CyberAgent Ca...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>264</td>\n",
       "      <td>要出发</td>\n",
       "      <td>Yaochufa</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>广州</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>丁根芳</td>\n",
       "      <td>2011</td>\n",
       "      <td>众信旅游、红杉资本、创新工场</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>264</td>\n",
       "      <td>易久批</td>\n",
       "      <td>Yijiupi</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>王朝成</td>\n",
       "      <td>2014</td>\n",
       "      <td>美团点评、腾讯、贝塔斯曼</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>264</td>\n",
       "      <td>洋码头</td>\n",
       "      <td>yMatou</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>曾碧波</td>\n",
       "      <td>2009</td>\n",
       "      <td>远镜创投、赛富基金</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>264</td>\n",
       "      <td>转转</td>\n",
       "      <td>Zhuanzhuan</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>姚劲波</td>\n",
       "      <td>2015</td>\n",
       "      <td>腾讯</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>264</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>ZipRecruiter</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>洛杉矶</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd</td>\n",
       "      <td>2010</td>\n",
       "      <td>IVP (Institutional Venture Partners)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名          企业名称  Company Name  估值（亿人民币）     国家   城市    行业  \\\n",
       "25    25           车好多          CARS       600     中国   北京  电子商务   \n",
       "26    25       Coupang       Coupang       600     韩国   首尔  电子商务   \n",
       "28    25          Wish          Wish       600     美国  旧金山  电子商务   \n",
       "34    34           美菜网        Meicai       500     中国   北京  电子商务   \n",
       "39    34     Tokopedia     Tokopedia       500  印度尼西亚  雅加达  电子商务   \n",
       "..   ...           ...           ...       ...    ...  ...   ...   \n",
       "480  264           要出发      Yaochufa        70     中国   广州  电子商务   \n",
       "483  264           易久批       Yijiupi        70     中国   北京  电子商务   \n",
       "485  264           洋码头        yMatou        70     中国   上海  电子商务   \n",
       "491  264            转转    Zhuanzhuan        70     中国   北京  电子商务   \n",
       "493  264  ZipRecruiter  ZipRecruiter        70     美国  洛杉矶  电子商务   \n",
       "\n",
       "                                               掌门人/创始人  成立年份  \\\n",
       "25                                                 杨浩涌  2011   \n",
       "26                                             Bom Kim  2010   \n",
       "28                      Danny Zhang, Peter Szulczewski  2010   \n",
       "34                                                 刘传军  2014   \n",
       "39          Leontinus Alpha Edison, William Tanuwijaya  2009   \n",
       "..                                                 ...   ...   \n",
       "480                                                丁根芳  2011   \n",
       "483                                                王朝成  2014   \n",
       "485                                                曾碧波  2009   \n",
       "491                                                姚劲波  2015   \n",
       "493  Ian Siegel, Joe Edmonds, Ward Poulos, Willis Redd  2010   \n",
       "\n",
       "                                                部分投资机构  \n",
       "25                                  红杉资本、今日资本、IDG、经纬中国  \n",
       "26   SoftBank Investment Advisers, Altos Ventures, ...  \n",
       "28   Formation 8, GGV Capital, Founders Fund, DST G...  \n",
       "34                                      顺为资本、纪源资本、真格基金  \n",
       "39   Indonusa Dwitama, East Ventures, CyberAgent Ca...  \n",
       "..                                                 ...  \n",
       "480                                     众信旅游、红杉资本、创新工场  \n",
       "483                                       美团点评、腾讯、贝塔斯曼  \n",
       "485                                          远镜创投、赛富基金  \n",
       "491                                                 腾讯  \n",
       "493               IVP (Institutional Venture Partners)  \n",
       "\n",
       "[68 rows x 10 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "industry('电子商务')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 取出时间做成列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2000,\n",
       " 2001,\n",
       " 2002,\n",
       " 2003,\n",
       " 2004,\n",
       " 2005,\n",
       " 2006,\n",
       " 2007,\n",
       " 2008,\n",
       " 2009,\n",
       " 2010,\n",
       " 2011,\n",
       " 2012,\n",
       " 2013,\n",
       " 2014,\n",
       " 2015,\n",
       " 2016,\n",
       " 2017,\n",
       " 2018,\n",
       " 2019]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "成立年份=pd.unique(df['成立年份'])\n",
    "time_list =list(set(成立年份))\n",
    "time_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>25</td>\n",
       "      <td>平安医保科技</td>\n",
       "      <td>Ping An Healthcare Technology</td>\n",
       "      <td>600</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>健康科技</td>\n",
       "      <td>高菁</td>\n",
       "      <td>2016</td>\n",
       "      <td>IDG、思佰益、软银海外</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>GRAIL</td>\n",
       "      <td>GRAIL</td>\n",
       "      <td>550</td>\n",
       "      <td>美国</td>\n",
       "      <td>门洛帕克</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Jeffrey Huber</td>\n",
       "      <td>2016</td>\n",
       "      <td>Illumina, ARCH Venture Partners, 6 Dimensions ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Argo AI</td>\n",
       "      <td>Argo AI</td>\n",
       "      <td>500</td>\n",
       "      <td>美国</td>\n",
       "      <td>Harrisburg</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Bryan Salesky, Peter Rander</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen, Ford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>84</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>Hellobike</td>\n",
       "      <td>200</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>杨磊</td>\n",
       "      <td>2016</td>\n",
       "      <td>纪源资本、磐谷创投、愉悦资本、蚂蚁金服</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>84</td>\n",
       "      <td>Nuro</td>\n",
       "      <td>Nuro</td>\n",
       "      <td>200</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>机器人</td>\n",
       "      <td>Dave Ferguson, Jiajun Zhu</td>\n",
       "      <td>2016</td>\n",
       "      <td>Softbank Investment Advisors, Gaorong Capital,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>138</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>150</td>\n",
       "      <td>美国</td>\n",
       "      <td>帕洛阿尔托</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Chris Urmson, J. Andrew Bagnell, Sterling Ande...</td>\n",
       "      <td>2016</td>\n",
       "      <td>Greylock Partners, Sequoia Capital, Hyundai Mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>138</td>\n",
       "      <td>寒武纪科技</td>\n",
       "      <td>Cambricon</td>\n",
       "      <td>150</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>陈天石</td>\n",
       "      <td>2016</td>\n",
       "      <td>国投创业、阿里巴巴、联想创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>138</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Nigel Toon, Simon Knowles</td>\n",
       "      <td>2016</td>\n",
       "      <td>Amadeus Capital Partners, Atomico, Sequoia Cap...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>138</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>150</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Paolo Cerruti, Peter Carlsson</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen Group, Goldman Sachs, Seimens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>138</td>\n",
       "      <td>小马智行</td>\n",
       "      <td>Pony.ai</td>\n",
       "      <td>150</td>\n",
       "      <td>美国</td>\n",
       "      <td>菲蒙市</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>彭军 、楼天城</td>\n",
       "      <td>2016</td>\n",
       "      <td>Legend Capital, ClearVue Partners , Kunlun, Mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>264</td>\n",
       "      <td>空中云汇</td>\n",
       "      <td>Airwallex</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jack Zhang</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、红杉资本、DST、高瓴资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>264</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Fair</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>圣塔莫尼卡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Boone Park, Craig Nehamen, Georg Bauer, Jennif...</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sherpa Capital, Softbank Investment Advisors, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>264</td>\n",
       "      <td>HMD</td>\n",
       "      <td>HMD</td>\n",
       "      <td>70</td>\n",
       "      <td>芬兰</td>\n",
       "      <td>赫尔辛基</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Jean-Francois Baril</td>\n",
       "      <td>2016</td>\n",
       "      <td>Ginko Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>264</td>\n",
       "      <td>氪空间</td>\n",
       "      <td>Kr Space</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>刘成城</td>\n",
       "      <td>2016</td>\n",
       "      <td>IDG、歌斐资产</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>264</td>\n",
       "      <td>联易融</td>\n",
       "      <td>Linklogis</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>宋群</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、泛海投资、中信资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>264</td>\n",
       "      <td>Meero</td>\n",
       "      <td>Meero</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Thomas Rebaud</td>\n",
       "      <td>2016</td>\n",
       "      <td>Avenir Growth Capital, Eurazeo Prime Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>264</td>\n",
       "      <td>Momenta</td>\n",
       "      <td>Momenta</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>曹旭东</td>\n",
       "      <td>2016</td>\n",
       "      <td>创新工场、腾讯、真格基金、顺为资本、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>264</td>\n",
       "      <td>Rappi</td>\n",
       "      <td>Rappi</td>\n",
       "      <td>70</td>\n",
       "      <td>哥伦比亚</td>\n",
       "      <td>波哥大</td>\n",
       "      <td>物流</td>\n",
       "      <td>Felipe Villamarin, Sebastian Mejia, Simon Borrero</td>\n",
       "      <td>2016</td>\n",
       "      <td>SoftBank, SoftBank Investment Advisers, Y Comb...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>264</td>\n",
       "      <td>Seismic</td>\n",
       "      <td>Seismic</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>圣地亚哥</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Rich Mahoney</td>\n",
       "      <td>2016</td>\n",
       "      <td>Jackson Square Ventures, JMI Equity, General A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>264</td>\n",
       "      <td>水滴</td>\n",
       "      <td>Shuidi</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>沈鹏</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、创新工场、IDG、美团点评</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>264</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Amod Malviya, Sujeet kumar, Vaibhav Gupta</td>\n",
       "      <td>2016</td>\n",
       "      <td>Lightspeed Venture Partners, DST Global</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名       企业名称                   Company Name  估值（亿人民币）    国家  \\\n",
       "27    25     平安医保科技  Ping An Healthcare Technology       600    中国   \n",
       "30    30      GRAIL                          GRAIL       550    美国   \n",
       "33    34    Argo AI                        Argo AI       500    美国   \n",
       "99    84       哈啰出行                      Hellobike       200    中国   \n",
       "109   84       Nuro                           Nuro       200    美国   \n",
       "143  138     Aurora                         Aurora       150    美国   \n",
       "153  138      寒武纪科技                      Cambricon       150    中国   \n",
       "172  138  Graphcore                      Graphcore       150    英国   \n",
       "196  138  Northvolt                      Northvolt       150    瑞典   \n",
       "200  138       小马智行                        Pony.ai       150    美国   \n",
       "273  264       空中云汇                      Airwallex        70    中国   \n",
       "331  264       Fair                           Fair        70    美国   \n",
       "349  264        HMD                            HMD        70    芬兰   \n",
       "378  264        氪空间                       Kr Space        70    中国   \n",
       "386  264        联易融                      Linklogis        70    中国   \n",
       "396  264      Meero                          Meero        70    法国   \n",
       "403  264    Momenta                        Momenta        70    中国   \n",
       "427  264      Rappi                          Rappi        70  哥伦比亚   \n",
       "436  264    Seismic                        Seismic        70    美国   \n",
       "439  264         水滴                         Shuidi        70    中国   \n",
       "465  264      Udaan                          Udaan        70    印度   \n",
       "\n",
       "             城市    行业                                            掌门人/创始人  \\\n",
       "27           上海  健康科技                                                 高菁   \n",
       "30         门洛帕克  生命科学                                      Jeffrey Huber   \n",
       "33   Harrisburg  人工智能                        Bryan Salesky, Peter Rander   \n",
       "99           上海  共享经济                                                 杨磊   \n",
       "109         旧金山   机器人                          Dave Ferguson, Jiajun Zhu   \n",
       "143       帕洛阿尔托  人工智能  Chris Urmson, J. Andrew Bagnell, Sterling Ande...   \n",
       "153          北京  人工智能                                                陈天石   \n",
       "172       布里斯托尔  人工智能                          Nigel Toon, Simon Knowles   \n",
       "196       斯德哥尔摩   新能源                      Paolo Cerruti, Peter Carlsson   \n",
       "200         菲蒙市  人工智能                                            彭军 、楼天城   \n",
       "273          香港  金融科技                                         Jack Zhang   \n",
       "331       圣塔莫尼卡  电子商务  Boone Park, Craig Nehamen, Georg Bauer, Jennif...   \n",
       "349        赫尔辛基   消费品                                Jean-Francois Baril   \n",
       "378          北京  共享经济                                                刘成城   \n",
       "386          深圳  金融科技                                                 宋群   \n",
       "396          巴黎  人工智能                                      Thomas Rebaud   \n",
       "403          北京  人工智能                                                曹旭东   \n",
       "427         波哥大    物流  Felipe Villamarin, Sebastian Mejia, Simon Borrero   \n",
       "436        圣地亚哥  人工智能                                       Rich Mahoney   \n",
       "439          北京  金融科技                                                 沈鹏   \n",
       "465        班加罗尔  电子商务          Amod Malviya, Sujeet kumar, Vaibhav Gupta   \n",
       "\n",
       "     成立年份                                             部分投资机构  \n",
       "27   2016                                       IDG、思佰益、软银海外  \n",
       "30   2016  Illumina, ARCH Venture Partners, 6 Dimensions ...  \n",
       "33   2016                                   Volkswagen, Ford  \n",
       "99   2016                                纪源资本、磐谷创投、愉悦资本、蚂蚁金服  \n",
       "109  2016  Softbank Investment Advisors, Gaorong Capital,...  \n",
       "143  2016  Greylock Partners, Sequoia Capital, Hyundai Mo...  \n",
       "153  2016                                     国投创业、阿里巴巴、联想创投  \n",
       "172  2016  Amadeus Capital Partners, Atomico, Sequoia Cap...  \n",
       "196  2016           Volkswagen Group, Goldman Sachs, Seimens  \n",
       "200  2016  Legend Capital, ClearVue Partners , Kunlun, Mo...  \n",
       "273  2016                                   腾讯、红杉资本、DST、高瓴资本  \n",
       "331  2016  Sherpa Capital, Softbank Investment Advisors, ...  \n",
       "349  2016                                     Ginko Ventures  \n",
       "378  2016                                           IDG、歌斐资产  \n",
       "386  2016                                       腾讯、泛海投资、中信资本  \n",
       "396  2016      Avenir Growth Capital, Eurazeo Prime Ventures  \n",
       "403  2016                             创新工场、腾讯、真格基金、顺为资本、纪源资本  \n",
       "427  2016  SoftBank, SoftBank Investment Advisers, Y Comb...  \n",
       "436  2016  Jackson Square Ventures, JMI Equity, General A...  \n",
       "439  2016                                   腾讯、创新工场、IDG、美团点评  \n",
       "465  2016            Lightspeed Venture Partners, DST Global  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['成立年份'].isin([\"2016\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time(i):\n",
    "    成立年份=pd.unique(df['成立年份'])\n",
    "    time_list =list(set(成立年份))\n",
    "    if i in time_list:\n",
    "        time_choose=df[df['成立年份'].isin([i])]\n",
    "        return time_choose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>25</td>\n",
       "      <td>平安医保科技</td>\n",
       "      <td>Ping An Healthcare Technology</td>\n",
       "      <td>600</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>健康科技</td>\n",
       "      <td>高菁</td>\n",
       "      <td>2016</td>\n",
       "      <td>IDG、思佰益、软银海外</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30</td>\n",
       "      <td>GRAIL</td>\n",
       "      <td>GRAIL</td>\n",
       "      <td>550</td>\n",
       "      <td>美国</td>\n",
       "      <td>门洛帕克</td>\n",
       "      <td>生命科学</td>\n",
       "      <td>Jeffrey Huber</td>\n",
       "      <td>2016</td>\n",
       "      <td>Illumina, ARCH Venture Partners, 6 Dimensions ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Argo AI</td>\n",
       "      <td>Argo AI</td>\n",
       "      <td>500</td>\n",
       "      <td>美国</td>\n",
       "      <td>Harrisburg</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Bryan Salesky, Peter Rander</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen, Ford</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>84</td>\n",
       "      <td>哈啰出行</td>\n",
       "      <td>Hellobike</td>\n",
       "      <td>200</td>\n",
       "      <td>中国</td>\n",
       "      <td>上海</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>杨磊</td>\n",
       "      <td>2016</td>\n",
       "      <td>纪源资本、磐谷创投、愉悦资本、蚂蚁金服</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>84</td>\n",
       "      <td>Nuro</td>\n",
       "      <td>Nuro</td>\n",
       "      <td>200</td>\n",
       "      <td>美国</td>\n",
       "      <td>旧金山</td>\n",
       "      <td>机器人</td>\n",
       "      <td>Dave Ferguson, Jiajun Zhu</td>\n",
       "      <td>2016</td>\n",
       "      <td>Softbank Investment Advisors, Gaorong Capital,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>138</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>Aurora</td>\n",
       "      <td>150</td>\n",
       "      <td>美国</td>\n",
       "      <td>帕洛阿尔托</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Chris Urmson, J. Andrew Bagnell, Sterling Ande...</td>\n",
       "      <td>2016</td>\n",
       "      <td>Greylock Partners, Sequoia Capital, Hyundai Mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>138</td>\n",
       "      <td>寒武纪科技</td>\n",
       "      <td>Cambricon</td>\n",
       "      <td>150</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>陈天石</td>\n",
       "      <td>2016</td>\n",
       "      <td>国投创业、阿里巴巴、联想创投</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>138</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>Graphcore</td>\n",
       "      <td>150</td>\n",
       "      <td>英国</td>\n",
       "      <td>布里斯托尔</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Nigel Toon, Simon Knowles</td>\n",
       "      <td>2016</td>\n",
       "      <td>Amadeus Capital Partners, Atomico, Sequoia Cap...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>138</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>Northvolt</td>\n",
       "      <td>150</td>\n",
       "      <td>瑞典</td>\n",
       "      <td>斯德哥尔摩</td>\n",
       "      <td>新能源</td>\n",
       "      <td>Paolo Cerruti, Peter Carlsson</td>\n",
       "      <td>2016</td>\n",
       "      <td>Volkswagen Group, Goldman Sachs, Seimens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>138</td>\n",
       "      <td>小马智行</td>\n",
       "      <td>Pony.ai</td>\n",
       "      <td>150</td>\n",
       "      <td>美国</td>\n",
       "      <td>菲蒙市</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>彭军 、楼天城</td>\n",
       "      <td>2016</td>\n",
       "      <td>Legend Capital, ClearVue Partners , Kunlun, Mo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>264</td>\n",
       "      <td>空中云汇</td>\n",
       "      <td>Airwallex</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>Jack Zhang</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、红杉资本、DST、高瓴资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>264</td>\n",
       "      <td>Fair</td>\n",
       "      <td>Fair</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>圣塔莫尼卡</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Boone Park, Craig Nehamen, Georg Bauer, Jennif...</td>\n",
       "      <td>2016</td>\n",
       "      <td>Sherpa Capital, Softbank Investment Advisors, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>349</th>\n",
       "      <td>264</td>\n",
       "      <td>HMD</td>\n",
       "      <td>HMD</td>\n",
       "      <td>70</td>\n",
       "      <td>芬兰</td>\n",
       "      <td>赫尔辛基</td>\n",
       "      <td>消费品</td>\n",
       "      <td>Jean-Francois Baril</td>\n",
       "      <td>2016</td>\n",
       "      <td>Ginko Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>264</td>\n",
       "      <td>氪空间</td>\n",
       "      <td>Kr Space</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>共享经济</td>\n",
       "      <td>刘成城</td>\n",
       "      <td>2016</td>\n",
       "      <td>IDG、歌斐资产</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>264</td>\n",
       "      <td>联易融</td>\n",
       "      <td>Linklogis</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>宋群</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、泛海投资、中信资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>264</td>\n",
       "      <td>Meero</td>\n",
       "      <td>Meero</td>\n",
       "      <td>70</td>\n",
       "      <td>法国</td>\n",
       "      <td>巴黎</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Thomas Rebaud</td>\n",
       "      <td>2016</td>\n",
       "      <td>Avenir Growth Capital, Eurazeo Prime Ventures</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>264</td>\n",
       "      <td>Momenta</td>\n",
       "      <td>Momenta</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>曹旭东</td>\n",
       "      <td>2016</td>\n",
       "      <td>创新工场、腾讯、真格基金、顺为资本、纪源资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>264</td>\n",
       "      <td>Rappi</td>\n",
       "      <td>Rappi</td>\n",
       "      <td>70</td>\n",
       "      <td>哥伦比亚</td>\n",
       "      <td>波哥大</td>\n",
       "      <td>物流</td>\n",
       "      <td>Felipe Villamarin, Sebastian Mejia, Simon Borrero</td>\n",
       "      <td>2016</td>\n",
       "      <td>SoftBank, SoftBank Investment Advisers, Y Comb...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>264</td>\n",
       "      <td>Seismic</td>\n",
       "      <td>Seismic</td>\n",
       "      <td>70</td>\n",
       "      <td>美国</td>\n",
       "      <td>圣地亚哥</td>\n",
       "      <td>人工智能</td>\n",
       "      <td>Rich Mahoney</td>\n",
       "      <td>2016</td>\n",
       "      <td>Jackson Square Ventures, JMI Equity, General A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>264</td>\n",
       "      <td>水滴</td>\n",
       "      <td>Shuidi</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>沈鹏</td>\n",
       "      <td>2016</td>\n",
       "      <td>腾讯、创新工场、IDG、美团点评</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>465</th>\n",
       "      <td>264</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>Udaan</td>\n",
       "      <td>70</td>\n",
       "      <td>印度</td>\n",
       "      <td>班加罗尔</td>\n",
       "      <td>电子商务</td>\n",
       "      <td>Amod Malviya, Sujeet kumar, Vaibhav Gupta</td>\n",
       "      <td>2016</td>\n",
       "      <td>Lightspeed Venture Partners, DST Global</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名       企业名称                   Company Name  估值（亿人民币）    国家  \\\n",
       "27    25     平安医保科技  Ping An Healthcare Technology       600    中国   \n",
       "30    30      GRAIL                          GRAIL       550    美国   \n",
       "33    34    Argo AI                        Argo AI       500    美国   \n",
       "99    84       哈啰出行                      Hellobike       200    中国   \n",
       "109   84       Nuro                           Nuro       200    美国   \n",
       "143  138     Aurora                         Aurora       150    美国   \n",
       "153  138      寒武纪科技                      Cambricon       150    中国   \n",
       "172  138  Graphcore                      Graphcore       150    英国   \n",
       "196  138  Northvolt                      Northvolt       150    瑞典   \n",
       "200  138       小马智行                        Pony.ai       150    美国   \n",
       "273  264       空中云汇                      Airwallex        70    中国   \n",
       "331  264       Fair                           Fair        70    美国   \n",
       "349  264        HMD                            HMD        70    芬兰   \n",
       "378  264        氪空间                       Kr Space        70    中国   \n",
       "386  264        联易融                      Linklogis        70    中国   \n",
       "396  264      Meero                          Meero        70    法国   \n",
       "403  264    Momenta                        Momenta        70    中国   \n",
       "427  264      Rappi                          Rappi        70  哥伦比亚   \n",
       "436  264    Seismic                        Seismic        70    美国   \n",
       "439  264         水滴                         Shuidi        70    中国   \n",
       "465  264      Udaan                          Udaan        70    印度   \n",
       "\n",
       "             城市    行业                                            掌门人/创始人  \\\n",
       "27           上海  健康科技                                                 高菁   \n",
       "30         门洛帕克  生命科学                                      Jeffrey Huber   \n",
       "33   Harrisburg  人工智能                        Bryan Salesky, Peter Rander   \n",
       "99           上海  共享经济                                                 杨磊   \n",
       "109         旧金山   机器人                          Dave Ferguson, Jiajun Zhu   \n",
       "143       帕洛阿尔托  人工智能  Chris Urmson, J. Andrew Bagnell, Sterling Ande...   \n",
       "153          北京  人工智能                                                陈天石   \n",
       "172       布里斯托尔  人工智能                          Nigel Toon, Simon Knowles   \n",
       "196       斯德哥尔摩   新能源                      Paolo Cerruti, Peter Carlsson   \n",
       "200         菲蒙市  人工智能                                            彭军 、楼天城   \n",
       "273          香港  金融科技                                         Jack Zhang   \n",
       "331       圣塔莫尼卡  电子商务  Boone Park, Craig Nehamen, Georg Bauer, Jennif...   \n",
       "349        赫尔辛基   消费品                                Jean-Francois Baril   \n",
       "378          北京  共享经济                                                刘成城   \n",
       "386          深圳  金融科技                                                 宋群   \n",
       "396          巴黎  人工智能                                      Thomas Rebaud   \n",
       "403          北京  人工智能                                                曹旭东   \n",
       "427         波哥大    物流  Felipe Villamarin, Sebastian Mejia, Simon Borrero   \n",
       "436        圣地亚哥  人工智能                                       Rich Mahoney   \n",
       "439          北京  金融科技                                                 沈鹏   \n",
       "465        班加罗尔  电子商务          Amod Malviya, Sujeet kumar, Vaibhav Gupta   \n",
       "\n",
       "     成立年份                                             部分投资机构  \n",
       "27   2016                                       IDG、思佰益、软银海外  \n",
       "30   2016  Illumina, ARCH Venture Partners, 6 Dimensions ...  \n",
       "33   2016                                   Volkswagen, Ford  \n",
       "99   2016                                纪源资本、磐谷创投、愉悦资本、蚂蚁金服  \n",
       "109  2016  Softbank Investment Advisors, Gaorong Capital,...  \n",
       "143  2016  Greylock Partners, Sequoia Capital, Hyundai Mo...  \n",
       "153  2016                                     国投创业、阿里巴巴、联想创投  \n",
       "172  2016  Amadeus Capital Partners, Atomico, Sequoia Cap...  \n",
       "196  2016           Volkswagen Group, Goldman Sachs, Seimens  \n",
       "200  2016  Legend Capital, ClearVue Partners , Kunlun, Mo...  \n",
       "273  2016                                   腾讯、红杉资本、DST、高瓴资本  \n",
       "331  2016  Sherpa Capital, Softbank Investment Advisors, ...  \n",
       "349  2016                                     Ginko Ventures  \n",
       "378  2016                                           IDG、歌斐资产  \n",
       "386  2016                                       腾讯、泛海投资、中信资本  \n",
       "396  2016      Avenir Growth Capital, Eurazeo Prime Ventures  \n",
       "403  2016                             创新工场、腾讯、真格基金、顺为资本、纪源资本  \n",
       "427  2016  SoftBank, SoftBank Investment Advisers, Y Comb...  \n",
       "436  2016  Jackson Square Ventures, JMI Equity, General A...  \n",
       "439  2016                                   腾讯、创新工场、IDG、美团点评  \n",
       "465  2016            Lightspeed Venture Partners, DST Global  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time(2016)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 生成总函数并画图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>排名</th>\n",
       "      <th>企业名称</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>估值（亿人民币）</th>\n",
       "      <th>国家</th>\n",
       "      <th>城市</th>\n",
       "      <th>行业</th>\n",
       "      <th>掌门人/创始人</th>\n",
       "      <th>成立年份</th>\n",
       "      <th>部分投资机构</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>蚂蚁金服</td>\n",
       "      <td>Ant Financial</td>\n",
       "      <td>10000</td>\n",
       "      <td>中国</td>\n",
       "      <td>杭州</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>井贤栋</td>\n",
       "      <td>2014</td>\n",
       "      <td>春华资本、中投海外、红杉资本</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>微众银行</td>\n",
       "      <td>WeBank</td>\n",
       "      <td>1500</td>\n",
       "      <td>中国</td>\n",
       "      <td>深圳</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>顾敏</td>\n",
       "      <td>2014</td>\n",
       "      <td>腾讯、华平投资、淡马锡</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>264</td>\n",
       "      <td>百融金服</td>\n",
       "      <td>100credit</td>\n",
       "      <td>70</td>\n",
       "      <td>中国</td>\n",
       "      <td>北京</td>\n",
       "      <td>金融科技</td>\n",
       "      <td>张韶峰</td>\n",
       "      <td>2014</td>\n",
       "      <td>中国国新、中金前海、红杉资本、IDG、高瓴资本</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      排名  企业名称   Company Name  估值（亿人民币）  国家  城市    行业 掌门人/创始人  成立年份  \\\n",
       "0      1  蚂蚁金服  Ant Financial     10000  中国  杭州  金融科技     井贤栋  2014   \n",
       "10    11  微众银行         WeBank      1500  中国  深圳  金融科技      顾敏  2014   \n",
       "263  264  百融金服      100credit        70  中国  北京  金融科技     张韶峰  2014   \n",
       "\n",
       "                      部分投资机构  \n",
       "0             春华资本、中投海外、红杉资本  \n",
       "10               腾讯、华平投资、淡马锡  \n",
       "263  中国国新、中金前海、红杉资本、IDG、高瓴资本  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df[df[['国家','行业','成立年份']].isin([\"日本\",\"电子商务\",\"2016\"])]\n",
    "df[(df['国家'] == \"中国\") & (df['行业'] == \"金融科技\")& (df['成立年份'] == 2014)]\n",
    "# df_筛选=df[df[['国家','行业','成立年份']].isin([\"中国\",\"健康科技\",2016])]\n",
    "# df_去重 = df_筛选.dropna(axis=0,how='all')\n",
    "# df_去重"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "def zong(country,industry,time):\n",
    "    国家=pd.unique(df['国家'])\n",
    "    country_list =list(set(国家))\n",
    "    行业=pd.unique(df['行业'])\n",
    "    industry_list =list(set(行业))\n",
    "    成立年份=pd.unique(df['成立年份'])\n",
    "    time_list =list(set(成立年份))\n",
    "    zong_list =[country_list,industry_list,time_list]\n",
    "    country in zong_list[0]\n",
    "    industry in zong_list[1]\n",
    "    time in zong_list[2]\n",
    "    choose=df[(df['国家'] ==country ) & (df['行业'] == industry)& (df['成立年份'] == time)]\n",
    "    return choose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>70</td>\n",
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       "      <td>香港</td>\n",
       "      <td>金融科技</td>\n",
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      "text/plain": [
       "      排名  企业名称 Company Name  估值（亿人民币）  国家  城市    行业     掌门人/创始人  成立年份  \\\n",
       "273  264  空中云汇    Airwallex        70  中国  香港  金融科技  Jack Zhang  2016   \n",
       "386  264   联易融    Linklogis        70  中国  深圳  金融科技          宋群  2016   \n",
       "439  264    水滴       Shuidi        70  中国  北京  金融科技          沈鹏  2016   \n",
       "\n",
       "               部分投资机构  \n",
       "273  腾讯、红杉资本、DST、高瓴资本  \n",
       "386      腾讯、泛海投资、中信资本  \n",
       "439  腾讯、创新工场、IDG、美团点评  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "筛选=zong(\"中国\",\"金融科技\",2016)\n",
    "筛选"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>企业数量</th>\n",
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       "    <tr>\n",
       "      <th>排名</th>\n",
       "      <th>国家</th>\n",
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       "      <th rowspan=\"3\" valign=\"top\">2016</th>\n",
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       "                                              估值（亿人民币）  企业数量\n",
       "排名  国家 行业   成立年份 掌门人/创始人    部分投资机构                          \n",
       "264 中国 金融科技 2016 Jack Zhang 腾讯、红杉资本、DST、高瓴资本        70     1\n",
       "                 宋群         腾讯、泛海投资、中信资本            70     1\n",
       "                 沈鹏         腾讯、创新工场、IDG、美团点评        70     1"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "结果=筛选[['排名','国家','城市','企业名称','行业','成立年份','估值（亿人民币）','掌门人/创始人','部分投资机构']]\\\n",
    ".groupby(['排名','国家','行业','成立年份','掌门人/创始人','部分投资机构'])\\\n",
    ".agg({'估值（亿人民币）':'sum','企业名称':'count'})\\\n",
    ".sort_values(['估值（亿人民币）','企业名称'],ascending=False)\\\n",
    ".rename ( columns = {\"企业名称\":\"企业数量\"} )\n",
    "结果"
   ]
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   "source": [
    "筛选.iplot(kind=\"bar\", x=[\"城市\"], y=\"估值（亿人民币）\", asFigure=True)"
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   "cell_type": "markdown",
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    "### 函数筛选器模型说明\n",
    "取出国家、行业 、年份的相关数据，整合成一个函数。  \n",
    "依次选择任一国家、行业、年份的数据，生成筛选数据。  \n",
    "对筛选数据进行进一步分析，分类聚合，并进行画图。    "
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